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Query Performance Prediction Using Reference Lists

The task of query performance prediction is to estimate the effectiveness of search performed in response to a query when no relevance judgments are... (more)

Probabilistic Models for Contextual Agreement in Preferences

The long-tail theory for consumer demand implies the need for more accurate personalization technologies to target items to the users who most desire... (more)

Examining Additivity and Weak Baselines

We present a study of which baseline to use when testing a new retrieval technique. In contrast to past work, we show that measuring a statistically significant improvement over a weak baseline is not a good predictor of whether a similar improvement will be measured on a strong baseline. Sometimes strong baselines are made worse when a new... (more)

Measuring the Semantic Uncertainty of News Events for Evolution Potential Estimation

The evolution potential estimation of news events can support the decision making of both corporations and governments. For example, a corporation... (more)

Diversifying Query Auto-Completion

Query auto-completion assists web search users in formulating queries with a few keystrokes, helping them to avoid spelling mistakes and to produce clear query expressions, and so on. Previous work on query auto-completion mainly centers around returning a list of completions to users, aiming to push queries that are most likely intended by the... (more)

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Call for Papers

ACM Transactions on Information Systems (TOIS) Call for submissions to a Special Issue on Search, Mining and their Applications on Mobile Devices. Click here to see more details.

Call for Special Issue Proposals

ACM Transactions on Information Systems (TOIS) invites proposals for a special issue of the journal devoted to any topic in information retrieval. Click here to see more details.

New options for ACM authors to manage rights and permissions for their work

 

ACM introduces a new publishing license agreement, an updated copyright transfer agreement, and a new authorpays option which allows for perpetual open access through the ACM Digital Library. For more information, visit the ACM Author Rights webpage.

 

About TOIS

ACM Transactions on Information Systems (TOIS) is a scholarly journal that publishes previously unpublished high-quality scholarly articles in all areas of information retrieval. TOIS is published quarterly.

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Forthcoming Articles
A Probabilistic Lifestyle-based Trajectory Model for Social Strength Inference from Human Trajectory Data

In this paper, we propose a probabilistic generative model to mine latent lifestyle-related patterns from human trajectory data for inferring social strength. It can automatically learn functionality topics consisting of locations with similar service functions and transition probabilities over the set of functionality topics. Furthermore, a lifestyle is modeled as a unique transition probability matrix over the set of functionality topics. A user has a preference distribution over the set of lifestyles, and she is able to select over multiple lifestyles to adapt to different living contexts. The learnt lifestyle-related patterns are subsequently used as features in a supervised learner for both strength estimation and link prediction. We conduct extensive experiments to evaluate the performance of the proposed method on two real-world datasets. The experimental results demonstrate the effectiveness of our proposed method.

Causal Relationship Detection in Archival Collections of Product Reviews for Understanding Technology Evolution

Technology progress is one of the key reasons behind rapid changes in our lifestyles these days. Knowing how products and objects evolve can not only help us in understanding the evolutionary patterns in our society but also provide us with clues on effective product design and support us in predicting the future. We propose here a general framework for analyzing technology impact on our lives through detecting cause-effect relationships where causes represent changes in technology, while effects are changes in society life such as new activities or new ways of using products. We address the challenge of viewing technology evolution through the social lens by mining causal relationships from the long-term collections of product reviews. We search for causal word pairs in which the change in the physical term triggers the change in the conceptual term. We then finally extend our approach to finding causal relationships between word groups such as group of words representing the same technology causing a given conceptual change or group of words representing two different technologies that simultaneously co-cause social changes. We conduct experiments on different product types using the Amazon Product Review Dataset which spans from 1995 to 2013 and demonstrate that our approaches perform better than state-of-the-art baselines.

Joint Modeling of User Check-in Behaviors for Real-time Point-of-Interest Recommendation

Point-of-Interest (POI) recommendation has become an important means to help people discover attractive and interesting places, especially when users travel out of town. However, extreme sparsity of user-POI matrix creates a severe challenge. To cope with this challenge, we propose a unified probabilistic generative model, Topic-Region Model (TRM), to simultaneously discover the semantic, temporal and spatial patterns of users' check-in activities, and to model their joint effect on users' decision-making for selection of POIs to visit. To demonstrate the applicability and flexibility of TRM, we investigate how it supports two recommendation scenarios in a unified way, i.e., home-town recommendation and out-of-town recommendation. To support real-time POI recommendation, we further extend the TRM model to an online learning model TRM-Online to track changing user interests and speed up the model training. Besides, based on the learnt model, we propose a clustering-based branch and bound algorithm (CBB) to prune the POI search space and facilitate fast retrieval of the top-k recommendations. We conduct extensive experiments to evaluate the performance of our proposals on two real-world datasets including recommendation effectiveness, overcoming cold-start problem, recommendation efficiency and model training efficiency. The experimental results demonstrate the superiority of our proposals.

Ranking-oriented Collaborative Filtering: A Listwise Approach

Conventional memory-based ranking-oriented Collaborative filtering (CF) can be referred to as pairwise algorithms. They represent each user as a set of preferences on each pair of items for similarity calculations and predictions. In this study, we propose ListCF, a novel listwise CF algorithm that seeks improvement in both accuracy and efficiency. In ListCF, each user is represented as a probability distribution of the permutations over rated items based on the Plackett-Luce model, and the similarity between users is measured based on the Kullback-Leibler (KL) divergence between their probability distributions over the set of commonly rated items. Given a target user and the most similar users, ListCF directly predicts a total order of items for each user based on similar users' probability distributions over permutations of the items. Besides, we also reveal insightful connections among pointwise, pairwise and listwise CF algorithms from the perspective of the matrix representations. In addition, to make our algorithm more scalable, we present an incremental algorithm for ListCF, which allows to incrementally update the similarities between users when certain user submits a new rating or updates an existing rating. Extensive experiments on benchmark datasets in comparison with the state-of-the-art approaches demonstrate the promise of our approach.

Cross-Lingual Topic Discovery From Multilingual Search Engine Query Log

Nowadays major commercial search engines are operating in a multinational fashion to provide web search services for millions of users who compose search queries by different languages. Hence, search engine query log, which serves as the backbone of many search engine applications, records millions of users search history in a wide spectrum of human languages and demonstrates a strong multilingual phenomenon. However, with its salience, the multilingual nature of search engine query log is usually ignored by the existing works, which usually consider query log entries of different languages as being orthogonal and independent. This kind of oversimplified assumption heavily distorts the underlying structure of web search data. In this paper, we pioneer in recognition of the multilingual nature of query log and make the first attempt to cross the language barrier in query log. Both qualitative and quantitative experimental results show that the CL-QLM is able to effectively derive cross-lingual topics from multilingual query log and spawn a wide spectrum of new search engine applications.

Accounting for Language Changes over Time in Document Similarity Search

Given a query document, ranking the documents in a collection based on how similar they are to the query is an essential task with extensive applications. For collections that contain documents whose creation dates span several decades, this task is further complicated by the fact that the language changes over time. For example, many terms add or lose one or more senses to meet people's evolving needs. To address this problem, we present methods that take advantage of two types of information to account for the language change. The first is the citation network that often exists within the collection, which can be used to link related documents with significantly different creation dates (and hence different language use). The second is the changes in the usage frequency of terms that occur over time, which can indicate changes in their senses and uses. These methods utilize the above information while estimating the representation of both documents and terms within the context of non-probabilistic static and dynamic topic models. Our experiments on two real-world datasets that span more than 40 years show that our proposed methods improve the retrieval performance of existing models and that these improvements are statistically significant.

Social Question Answering: Textual, User, and Network Features for Best Answer Prediction

Community Question Answering (CQA) sites use a collaborative paradigm to satisfy complex information needs. Although the task of matching questions to their best answers has been tackled for more than a decade, the social question answering practice is a complex process. The factors inuencing the accuracy of question-answer matching are many and hard to disentangle. We approach the task from an application-oriented perspective, probing the space of several dimensions relevant to this problem: features, algorithms, and topics. We gather under a learning-to-rank framework the most extensive feature set used in literature to date, including 225 features from ve different families. We test the power of such features in predicting the best answer to a question on the largest dataset from Yahoo Answers used for this task so far (40M answers), and provide a faceted analysis of the results along different topical areas and question types. We propose a novel family of distributional semantics measures that can most of the times seamlessly replace widely used linguistic similarity features,being more than one order of magnitude faster to compute and providing greater predictive power. The best feature set reaches an improvement between 11% and 26% in P@1 compared to recent well-established state-of-the-art methods.

Trip Recommendation Meets Real World Constraints: POI Availability, Diversity and Traveling Time Uncertainty

As location-based social network (LBSN) services become increasingly popular, trip recommendation that recommends a sequence of points of interest (POIs) to visit for a user emerges as one of many important applications of LBSNs. Personalized trip recommendation tailors to users' specific tastes by learning from past check-in behaviors of users and their peers. Finding the optimal trip that maximizes user's experiences for a given time budget constraint is an NP hard problem and previous solutions do not consider two practical and important constraints. One constraint is POI availability where a POI may be only available during a certain time window. Another constraint is uncertain traveling time where the traveling time between two POIs is uncertain. Besides, the diversity of the POIs included in the trip also affect user's adoptions. This work presents efficient solutions to personalized trip recommendation by incorporating these constraints to prune the search space. We evaluated the efficiency and effectiveness of our solutions on real life LBSN data sets.

Comparing Pointwise and Listwise Objective Functions for Random Forest based Learning-to-Rank

Current random forest (RF) based learning-to-rank (LtR) algorithms use a classification or regression framework to solve the ranking problem in a pointwise manner. The success of this simple yet effective approach coupled with the inherent parallelizability of the learning algorithm makes it a strong candidate for widespread adoption. In this paper we aim to better understand the effectiveness of these algorithms by comparing between pointwise and listwise objective functions. We introduce what we believe to be the first listwise version of an RF-based LtR algorithm. The algorithm directly optimizes an information retrieval metric of choice in a greedy manner. Computational complexity of the listwise approach is higher than the pointwise counterpart, hence for larger datasets, we design a hybrid algorithm which combines listwise and pointwise objective in each tree. Experimental results reveal that the listwise/hybrid algorithm outperforms the pointwise approach on the majority (but not all) of LtR datasets available. We then investigate several aspects of the two algorithms to better understand the inevitable performance trade-offs. This investigation suggests that for large LtR datasets the splitting criterion (implied by the objective function) is important particularly if small trees are learnt, but as the trees are grown large the advantage of the listwise approach diminishes relative to its pointwise counterpart.

TopPRF: A Probabilistic Framework for Integrating Topic Space into Pseudo Relevance Feedback

Recently, topic modeling becomes more and more popular in the information retrieval (IR) and other related areas. In this paper, we first investigate a key factor of the fuzzy topic problem, the topic number for topic modeling and how it makes topics "fuzzy". A new concept Topic Space (TS) is also introduced to evaluate the reliability of each candidate feedback document. Then we propose a probabilistic framework "TopPRF" and three new models TS-COS, TS-EU and TS-Entropy via integrating "Topic Space information into Pseudo Relevance Feedback (PRF). The proposed framework and models will identify how reliable a document is to be relevant through both term and topic information, which allow us to search documents beyond traditional term matching only and provide a promising avenue for constructing better topic-space based IR systems. When selecting feedback terms, candidate terms in more reliable feedback documents should obtain extra weights. Extensive experiments on various public collections justify that our proposed methods can significantly reduce the influence of "fuzzy topics and also make significant improvements over strong baseline models with optimal parameter settings.

A Meta-Framework for Modeling the Human Reading Process in Sentiment Analysis

This paper introduces a sentiment analysis approach that adopts the way humans read, interpret and extract sentiment from text. Psychological studies indicate that humans use two phases of mental processing: low-level parsing followed by high-level interpretation that is combined with preconceived notions to extract sentiment. A full automation of the reading process is very complicated. Alternatively, we propose to automate the reading process with primary focus on sentiment interpretation with modeling preconceived notions. This automation involves the use of natural language processing (NLP) techniques for feature extraction, developing notions databases, and using machine learning algorithms for sentiment prediction. Key contributions include 1) modeling preconceived notions as {textual characteristic, sentiment score} combinations, 2) a method to develop notions databases and 3) a mapping of notion-centric reading process to sentiment analysis. The uniqueness of this approach lies in its ability to leverage NLP tools and resources and machine learning algorithms to automate cognitive processes based on established psychological theories. This methodology points the way towards the integration of psychology with computational linguistics and machine learning to employ models of pragmatics and discourse analysis for sentiment analysis. Results indicate the ability of this model to achieve better performance compared to other accurate models.

Answering Arabic Why-questions: Baseline vs. RST-based Approach

Question answering (QA) system is concerned with building a system that automatically answer questions posed by humans in a natural language. Compared to other languages, little effort was directed towards QA systems for Arabic. Due to the difficulty of handling why-questions, most Arabic QA systems tend to ignore it. In this paper, we specifically address the why-question for Arabic using two different approaches and compare their performance and the quality of their answer. The first approach is the baseline approach, and for the second approach we use Rhetorical Structure Theory (RST). We evaluate both schemes using a corpora of 700 textual documents in different genres collected from Open Source Arabic Corpora (OSAC), and a set of 100 question-answer pairs. Of these, we had 45 common questions where both schemes answered correctly, 19 of which were identically answered. For the remaining 26 questions, the RST-based approach managed better answers for over half the questions. Overall the RST-based approach achieved better recall and precision.

The Effects of Aggregated Search Coherence on Search Behavior

Aggregated search is the task of combining results from multiple independent search systems in a single search results page (SERP). Aggregated search coherence refers to the extent to which different sources on the SERP focus on similar senses of an ambiguous query. In previous studies, we found that the query-senses in a set of vertical results can influence user engagement with the web results (the so-called ``spillover'' effect). In this work, we investigate five research questions (RQ1-RQ5) that extend our prior work. First, we investigate the extent to which results from different sources focus on different senses of an ambiguous query (RQ1). Second, we investigate how the vertical-to-web spillover effect varies across different verticals (RQ2). Then, we examine whether the level of spillover depends on the vertical position (RQ3) and on whether the vertical results are displayed with a border and different-colored background to distinguish them from the web results (RQ4). Finally, we propose a new method for displaying results from a particular vertical that are more consistent with the query-senses in the web results (RQ5). We evaluate this new method based on how it influences users to make more correct decisions about their level of engagement with the web results.

Bibliometrics

Publication Years 1983-2016
Publication Count 630
Citation Count 19218
Available for Download 630
Downloads (6 weeks) 3641
Downloads (12 Months) 37757
Downloads (cumulative) 715253
Average downloads per article 1135
Average citations per article 31
First Name Last Name Award
Hal Berghel Outstanding Contribution to ACM Award (2000)
ACM Distinguished Service Award (1996)
Daniel Bobrow ACM Software System Award (1992)
ACM Programming Systems and Languages Paper Award (1974)
Kellogg S. Booth ACM Distinguished Member (2009)
ACM Senior Member (2009)
Carlos A. Castillo ACM Senior Member (2014)
Charles L A Clarke ACM Distinguished Member (2015)
Fabio Crestani ACM Senior Member (2009)
Ernesto Damiani ACM Distinguished Member (2008)
Susan T Dumais ACM-W Athena Lecturer Award (2014)
Ahmed Elmagarmid ACM Distinguished Member (2009)
Deborah Estrin ACM-W Athena Lecturer Award (2006)
Alvaro Barreiro Garcia ACM Senior Member (2009)
Calvin C. Gotlieb Outstanding Contribution to ACM Award (2011)
ACM Presidential Award (2002)
Wendy Hall Outstanding Contribution to ACM Award (2014)
Jonathan L Herlocker ACM Software System Award (2010)
Djoerd Hiemstra ACM Senior Member (2009)
Eric Horvitz ACM AAAI Allen Newell Award (2015)
Xian-Sheng Hua ACM Distinguished Member (2015)
ACM Senior Member (2009)
Min-Yen Kan ACM Senior Member (2009)
David Karger ACM Doctoral Dissertation Award (1994)
Won Kim ACM Distinguished Service Award (2001)
Jon Kleinberg ACM AAAI Allen Newell Award (2014)
ACM-Infosys Foundation Award in the Computing Sciences (2008)
Joseph A Konstan ACM Software System Award (2010)
ACM Distinguished Member (2006)
Wessel Kraaij ACM Senior Member (2007)
Raymond A Lorie ACM Software System Award (1988)
ACM Programming Systems and Languages Paper Award (1982)
David E. Losada ACM Senior Member (2011)
Yoelle Maarek ACM Distinguished Member (2010)
Gary Marchionini ACM Senior Member (2008)
Satoshi Matsuoka ACM Gordon Bell Prize
Tokyo Institute of Technology (2011) ACM Gordon Bell Prize
Tokyo Institute of Technology (2011)
Kathryn Mckinley ACM Distinguished Member (2006)
ACM Senior Member (2006)
Stuart Edward Middleton ACM Senior Member (2014)
George Andrei Mihaila ACM Senior Member (2008)
Bradley N Miller ACM Software System Award (2010)
Mario A Nascimento ACM Senior Member (2007)
Hwee Tou Ng ACM Distinguished Member (2010)
Dianne P O'Leary ACM Distinguished Member (2006)
Judith S Olson ACM-W Athena Lecturer Award (2011)
Randy Pausch ACM Karl V. Karlstrom Outstanding Educator Award (2007)
David M Pennock ACM Senior Member (2006)
Vijay V Raghavan ACM Distinguished Member (2012)
Paul J Resnick ACM Software System Award (2010)
John T Riedl ACM Software System Award (2010)
ACM Distinguished Member (2007)
Mehran Sahami ACM Presidential Award (2014)
Fabio A. Schreiber ACM Senior Member (2012)
Robert P. Schumaker ACM Senior Member (2012)
Frank Shipman ACM Distinguished Member (2009)
Michael Stonebraker ACM A. M. Turing Award (2014)
ACM Software System Award (1988)
Jaime Teevan ACM Senior Member (2012)
Loren Terveen ACM Distinguished Member (2009)
Jennifer Widom ACM-W Athena Lecturer Award (2015)
Qiang Yang ACM Distinguished Member (2011)
Shumin Zhai ACM Distinguished Member (2006)

First Name Last Name Paper Counts
Tatseng Chua 8
Justin Zobel 8
William Croft 8
Hsinchun Chen 8
Norbert Fuhr 7
Stavros Christodoulakis 6
Hector Garcia-Molina 6
Bin Cui 6
Kalervo Järvelin, 5
Gonzalo Navarro 5
Dennis Tsichritzis 5
Alistair Moffat 5
John Gould 5
Thomas, Malone 5
Roger King 5
Oren Kurland 4
John Leggett 4
Ophir Frieder 4
Dennis McLeod 4
Prasenjit Mitra 4
Hugh Williams 4
Susan Dumais 4
Ricardo Baeza-Yates 4
Ahmed Abbasi 4
Zi Huang 4
Fabio Crestani 4
ChengXiang Zhai 4
Maarten De Rijke 4
Kamfai Wong 4
Jimmy Lin 4
Hengtao Shen 4
Swapan Parui 3
Dawei Song 3
Luis Gravano 3
Fausto Rabitti 3
Elisa Bertino 3
Abdur Chowdhury 3
Joseph Konstan 3
Alexander Tuzhilin 3
Liqiang Nie 3
Amihai Motro 3
Heikki Keskustalo 3
Kumyew Lai 3
Luo Si 3
Nieves Brisaboa 3
Christos Faloutsos 3
Raffaele Perego 3
Fabrizio Silvestri 3
Ge Nong 3
Henry Gladney 3
Matthias Jarke 3
Roy Rada 3
Kuilam Kwok 3
Marjan Celikik 3
Robert Luk 3
Nívio Ziviani 3
Eric Horvitz 3
Abraham Bookstein 3
Simon Gibbs 3
Pavel Zezula 3
William Cohen 3
Edleno De Moura 3
Cornelis Van Rijsbergen 3
Shmuel Klein 3
Jamie Callan 3
Ben Shneiderman 3
Wai Lam 3
Gary Marchionini 3
Ryen White 3
Hannah Bast 3
Özgür Ulusoy 2
Zhiting Hu 2
Quan Yuan 2
Gao Cong 2
Raymond Panko 2
Robert Krovetz 2
Charles Wiecha 2
Fazli Can 2
Warren Greiff 2
Seungwon Hwang 2
Vijay Raghavan 2
Mark Chignell 2
Rong Jin 2
Eric Jensen 2
Panagiotis Ipeirotis 2
Sakti Pramanik 2
Alan Hevner 2
Jiaul Paik 2
Mandar Mitra 2
Loren Terveen 2
Carson Woo 2
David Hicks 2
Howard Turtle 2
Kotagiri Ramamohanarao 2
Wanda Orlikowski 2
Iadh Ounis 2
Fernando Diaz 2
David Carmel 2
Hong Cheng 2
William Webber 2
Barbara Pernici 2
Xiaojun Wan 2
Jaana Kekäläinen 2
Carmel Domshlak 2
Leefeng Chien 2
Antonio Fariña, 2
Zhaohui Zheng 2
Gediminas Adomavicius 2
Jinxi Xu 2
Shibing Yao 2
Clyde Giles 2
Sudha Ram 2
Padmini Srinivasan 2
Weiyi Meng 2
Jaime Teevan 2
Raymond Lau 2
Fred Damerau 2
Laurence Park 2
Keke Chen 2
Nick Craswell 2
Mark Sanderson 2
Nigel Shadbolt 2
Elena Baralis 2
Paolo Garza 2
Chirag Shah 2
Lucy Suchman 2
Antonio Siochi 2
Steven Beitzel 2
Scott Hudson 2
Joemon Jose 2
Nicole Yankelovich 2
Jianyun Nie 2
Shane Culpepper 2
Waihong Chan 2
Nat Ballou 2
Shipeng Li 2
Claudio Carpineto 2
Mansur Kabuka 2
Hui Yang 2
Christopher Higgins 2
Edward Dang 2
Gautam Pant 2
Jonathan Grudin 2
Hui Xiong 2
Benjamin Piwowarski 2
Filip Radlinski 2
Lillian Lee 2
Ian Ruthven 2
Stefan Siersdorfer 2
John Riedl 2
Frank Tompa 2
Frederick Lochovsky 2
Darrell Woelk 2
Ronny Lempel 2
Clayton Lewis 2
William Jones 2
Peter Bruza 2
Mounia Lalmas 2
Gordon Cormack 2
Yoelle Maarek 2
Arjen De Vries 2
Dou Shen 2
Paul Stotts 2
George Fitzmaurice 2
Olivia Sheng 2
John Mylopoulos 2
Anthony Kaye 2
Qiang Yang 2
John Schnase 2
Jennifer Widom 2
Ronan Cummins 2
Ismail Altingövde 2
Douglas Terry 2
Maria Fugini 2
Tao Mei 2
Javed Mostafa 2
Essam El-Kwae 2
John Carroll 2
Hongzhi Yin 2
Hochung Wu 2
Massimo Melucci 2
Pasquale Savino 2
Eepeng Lim 2
Hongyan Liu 2
Richard Furuta 2
Hideki Koike 2
Stephen Boies 2
Salvatore Orlando 2
Xiaofang Zhou 2
Edward Fox 2
Irwin King 2
Pável Calado 2
Tao Tao 2
Jiantao Sun 2
Susan Gauch 2
Manolis Koubarakis 2
Neil Rowe 2
Randall Trigg 2
Letizia Tanca 2
Dimitris Papadias 2
Jorge Garza 2
Won Kim 2
Giovanni Romano 2
Marcel Reinders 2
Stanley Zdonik 2
Berthier Ribeiro-Neto 2
Sanda Harabagiu 2
Piero Fraternali 2
Paolo Paolini 2
Ling Feng 2
Brian Cooper 2
Daniel Zeng 2
Thorsten Joachims 2
Michael Lyu 2
Jialie Shen 2
Stuart Middleton 2
Qiang Zhu 2
David Hawking 2
Shiqiang Yang 1
Satya Rachakonda 1
Catherine Plaisant 1
Katja Hofmann 1
Michael Chau 1
Elad Yom-Tov 1
Klaus Schulz 1
Francisco Claude 1
Ángeles Places 1
Ben Carterette 1
Weigang Wang 1
Yogen Dalal 1
Kaveh Pahlavan 1
Robert Neches 1
Xin Cao 1
Zhengjun Zha 1
Stephanie Haas 1
Waynexin Zhao 1
Stefano Leonardi 1
Piotr Sankowski 1
Sicong Zhang 1
Jiancong Tong 1
Parvaz Mahdabi 1
Zhongzhi Shi 1
Lars Söderlund 1
Matts Ahlsen 1
Pierre Genevès 1
Nabil Layaïda 1
Lise Getoor 1
Peter Schäuble 1
Ying Lu 1
Fiana Raiber 1
Taklam Wong 1
Dario Lucarella 1
Engin Demir 1
Shimon Schocken 1
Mary Culnan 1
Nevenka Dimitrova 1
Dick Bulterman 1
Author index 1
Julia Mayer 1
Qing Cui 1
Hanjun Dai 1
Alessandro Fiori 1
Xiaojun Quan 1
Pertti Vakkari 1
Alan Katz 1
Tomchao Zhou 1
David Vallet 1
Chris Horner 1
Harvey Brightman 1
Roi Blanco 1
Alan Smeaton 1
Hongbin Dai 1
Ling Liu 1
Stephen Robertson 1
Rachel Matichin 1
Gobinda Kole 1
Eduardo Rodríguez 1
Olivier Chapelle 1
Rifat Ozcan 1
Ian Witten 1
Dianne O'Leary 1
Ravichander Vipperla 1
Raphael Troncy 1
Michal Fapšo 1
Hyoungjoo Kim 1
Giampio Bracchi 1
Rudy Hirschheim 1
Mark Guttenbrunner 1
Nicola Orio 1
Scott Deerwester 1
Peter Bollmann 1
Federico Barbic 1
Aris Anagnostopoulos 1
Aleksandr Chuklin 1
Anne Schuth 1
Ke Zhou 1
Le Song 1
Bernhard Schölkopf 1
Ping Li 1
Shuguang Han 1
Eric Lo 1
Kevyn Collins-Thompson 1
Richong Zhang 1
Lise Getoor 1
Thomas Hofmann 1
Zan Huang 1
Börkur Sigurbjörnsson 1
Scott Stevens 1
Mark Dunlop 1
Douglas Brotz 1
František Grézl 1
Steven Shute 1
Joyce Reynolds 1
Gregory Finn 1
Jonathan Postel 1
Melody Ivory 1
Finley Lacatusu 1
Kermit Gilbert 1
Linda Fineman 1
Arno Peels 1
Xiao Li 1
Satoshi Matsuoka 1
Shin Takahashi 1
Jun He 1
Venkat Gudivada 1
Ramesh Choudhari 1
Allison Powell 1
Richard Chimera 1
O Wu 1
Tuomas Talvensaari 1
Georges Dupret 1
Laura Granka 1
Geri Gay 1
D Rama 1
Irene Greif 1
Daniel Bobrow 1
Stuart Weibel 1
Craig Macdonald 1
Iadh Ounis 1
Terri Hedgpeth 1
Maria Sapino 1
Kianlee Tan 1
Sadok Yahia 1
Vadims Krivcovs 1
Adam Edwards 1
Eva Jaho 1
Carlos Castillo 1
Deborah Barreau 1
Neill Kipp 1
Chengqi Zhang 1
Bruno De Araujo 1
Jonathan Slocum 1
Marko Rodriguez 1
Robert Schumaker 1
Prasun Dewan 1
Thomas Mastaglio 1
Mark Linton 1
José Gómez Hidalgo 1
Chunghsien Wu 1
Beb Galdes 1
Douglas Metzler 1
Mohamed Sarwat 1
Paul Over 1
James Thornton 1
Hal Berghel 1
Antonella Zanzi 1
Daniel Robey 1
Yiming Yang 1
Airi Salminen 1
Tomás Isakowitz 1
João Magalhães 1
Stefan Rüger 1
Yiyu Yao 1
S Wong 1
Andrew Whitsitt 1
Tomas Saulys 1
Michael Schrefl 1
Eugene Guglielmo 1
Steven Kimbrough 1
Forouzan Golshani 1
Bernard Hauzeur 1
Azhar Alhindi 1
Nicholas Belkin 1
Aixin Sun 1
Erkki Lehitnen 1
Jakob Gonczarowski 1
TeckTim Tan 1
Taesup Moon 1
Yingqin Gu 1
Gerald Barber 1
Andrew Bailey 1
Robert Purvy 1
Peter Turney 1
Kuldeep Karnawat 1
David Sturman 1
Martti Juhola 1
Sylvia Sheppard 1
Sunil Sarin 1
Peter Sassone 1
Lorraine Normore 1
Richard Entlich 1
Alda Gançarski 1
Steve Whittaker 1
Ralph Palmer 1
MC Schraefel 1
David Bodoff 1
Guirong Xue 1
Cornelis Van Rijsbergen 1
Craig Macdonald 1
Marc Bron 1
Bruce Ballard 1
James Farber 1
Susan Ehrlich 1
Guy Hochgesang 1
James Donahue 1
Elizabeth Chang 1
Sara Comai 1
George Herman 1
Fabio Schreiber 1
Peter Knees 1
Xin Yan 1
Xue Li 1
David Dupplaw 1
Nadene Lynn 1
Antonin Guttman 1
Hsiaowuen Hon 1
Xin Fu 1
Alexandra Poulovassilis 1
Mark Levene 1
Pamela Ludford 1
Rosie Jones 1
Yiliang Zhao 1
Alex Borgida 1
Hao Ma 1
Debby Hindus 1
James Coombs 1
Peter Hibbard 1
John Cookson 1
Mark Steyvers 1
Sergio Greco 1
Hyowon Lee 1
Zheng Ye 1
Jianying Wang 1
Shimon Whiteson 1
Fabrizio Sebastiani 1
Ornan Gerstel 1
Xiao Fang 1
Kalyankumar Datta 1
Quan Wang 1
Andreas Broschart 1
Abdul Shariff 1
Venkataraman Ramesh 1
Nicholas Evans 1
Xindong Wu 1
Shichao Zhang 1
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Bin Gao 1
M Albakour 1
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Mstislav Maslennikov 1
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Affiliation Paper Counts
San Francisco State University 1
Enel 1
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University of New South Wales 1
Universidad de Santiago de Compostela 1
Fairleigh Dickinson University 1
University of Ottawa, Canada 1
University of Athens 1
University of Hawaii System 1
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OMRON Corporation 1
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Universite de Lyon 1
Chemical Abstracts Service 1
MITRE Corporation 1
Norwegian University of Science and Technology 1
College of Charleston 1
INRIA Institut National de Rechereche en Informatique et en Automatique 1
Oregon State University 1
Institute of Information Science Academia Sinica Taiwan 1
University of Warsaw 1
Beihang University 1
University of Hawaii at Manoa 1
Sun Microsystems 1
Federal University of Uberlandia 1
University of Pavia 1
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University of Washington 1
Bentley College 1
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Philips Research 1
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Chinese Academy of Sciences 1
Monash University 1
Iona College 1
University of Liverpool 1
Jadavpur University 1
Universite Paris 1 Pantheon-Sorbonne 1
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The University of Warwick 1
Aalborg University 1
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Emerson College 1
University of Liege 1
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University of Helsinki 1
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Lehigh University 2
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Mayo Clinic 2
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Avaya Inc. 2
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BBN Technologies 2
Open University 2
INRIA Rhone-Alpes 2
National Chiao Tung University Taiwan 2
University of Texas at Austin 2
University of Massachusetts System 2
Drexel University 2
National Cheng Kung University 2
University of Louisiana at Lafayette 2
Weizmann Institute of Science Israel 2
The University of North Carolina System 2
Simon Fraser University 2
University of Wisconsin Milwaukee 2
University of Calabria 2
Xerox Research Centre Europe 2
University of Delaware 2
Waseda University 2
University of Iowa 2
University of Edinburgh 2
University of California, Los Angeles 2
University of Bologna 2
Universidad Europea de Madrid 2
Northeastern University 2
Ludwig Maximilian University of Munich 2
University of California, Santa Barbara 2
University of California, Riverside 2
University of Cambridge 2
Universite d'Avignon et des Pays du Vaucluse 2
California Institute of Technology 2
INRIA Rocquencourt 2
University of Sunderland 2
Shahid Beheshti University 2
Tunis-El Manar University 2
Max Planck Institute for Informatics 3
University of Essex 3
Los Alamos National Laboratory 3
Google Inc. 3
University of Mannheim 3
The University of North Carolina at Charlotte 3
Universitat Politecnica de Catalunya 3
Australian National University 3
University of Kansas 3
University of Texas at Dallas 3
Georgia State University 3
Ca' Foscari University of Venice 3
University of Duisburg-Essen 3
Academia Sinica Taiwan 3
Carleton University 3
Hong Kong Institute of Education 3
Vienna University of Technology 3
Southwest University of Finance and Economics China 3
Tianjin University 3
University of Reggio Calabria 3
Hewlett-Packard 3
Indiana University 3
Queen Mary, University of London 3
University College London 3
New Jersey Institute of Technology 3
Georgetown University 3
Dublin City University 3
Shanghai Jiaotong University 3
University of Sydney 3
Universidad Autonoma de Madrid 3
University of Oxford 3
Ben-Gurion University of the Negev 3
University of Illinois at Chicago 3
University of Miami 3
University of Bath 3
Syracuse University 3
University of California, San Diego 3
University of Nevada, Las Vegas 3
Pontifical Catholic University of Rio de Janeiro 3
Naval Postgraduate School 3
Nanjing University 3
National Center for Biotechnology Information 3
Aalto University 3
Federal University of Amazonas 4
University of Geneva 4
National Taiwan University 4
Delft University of Technology 4
University of Florida 4
Boston University 4
Binghamton University State University of New York 4
IBM 4
University of Strathclyde 4
Karlsruhe Institute of Technology, Campus South 4
EURECOM Ecole d'Ingenieurs & Centre de Recherche en Systemes de Communication 4
Columbia University 4
University of Copenhagen 4
University of Jyvaskyla 4
Fondazione Ugo Bordoni 4
Microsoft Research Cambridge 4
University of Illinois at Urbana-Champaign 5
University of Sheffield 5
University of Minnesota System 5
The University of British Columbia 5
The University of Western Ontario 5
Polytechnic Institute of Turin 5
Brno University of Technology 5
City University of Hong Kong 5
University of Southern California, Information Sciences Institute 5
University of Pittsburgh 5
Nankai University 5
University of Technology Sydney 5
University of Utah 5
IBM Haifa Labs 5
Pohang University of Science and Technology 5
University of Roma La Sapienza 5
University of Lugano 6
Duke University 6
Brown University 6
Renmin University of China 6
University of Washington Seattle 6
Singapore Management University 6
Xerox Corporation 6
University of Twente 6
Sun Yat-Sen University 6
National Chiayi University 6
Johannes Kepler University Linz 6
University of Freiburg 6
University of Chicago 6
University of Alberta 6
University at Buffalo, State University of New York 6
University of Padua 7
National Library of Medicine 7
Ohio State University 7
University of California, Irvine 7
Purdue University 7
Universidad de Chile 7
Bilkent University 7
Italian National Research Council 7
University of Virginia 7
University of California, Berkeley 7
University of Dortmund 7
Institute for Infocomm Research, A-Star, Singapore 8
IBM Almaden Research Center 8
Georgia Institute of Technology 8
Cardiff University 8
The University of North Carolina at Chapel Hill 8
Federal University of Minas Gerais 9
Rutgers University 9
Michigan State University 9
Illinois Institute of Technology 10
Arizona State University 10
Hong Kong Polytechnic University 10
Indian Statistical Institute, Kolkata 10
Tsinghua University 10
University of Milan 10
Pennsylvania State University 11
Nanyang Technological University 11
New York University 11
Universidad de A Coruna 11
Istituto di Scienza e Tecnologie dell'Informazione A. Faedo 11
University of Amsterdam 12
Hong Kong University of Science and Technology 12
Cornell University 13
Texas A and M University 13
Telcordia Technologies, Inc. 13
Microsoft 13
University of Melbourne 13
Virginia Tech 13
Microsoft Research Asia 13
University of Southern California 14
University of Colorado at Boulder 15
Carnegie Mellon University 15
University of Minnesota Twin Cities 15
University of Waterloo 16
University of Toronto 16
University of Glasgow 18
Peking University 18
Technion - Israel Institute of Technology 18
University of Southampton 18
Yahoo Research Labs 19
Microelectronics Computer Technology Corporation 20
RMIT University 20
Politecnico di Milano 20
University of Queensland 21
Stanford University 22
University of Tampere 23
Microsoft Research 23
University of Massachusetts Amherst 24
Massachusetts Institute of Technology 24
Palo Alto Research Center 24
Chinese University of Hong Kong 25
National University of Singapore 27
University of Arizona 28
IBM Thomas J. Watson Research Center 32
University of Maryland 34

ACM Transactions on Information Systems (TOIS)
Archive


2016
Volume 34 Issue 4, June 2016  Issue-in-Progress
Volume 34 Issue 3, May 2016 Special Issue on Trust and Veracity of Information in Social Media
Volume 34 Issue 2, April 2016

2015
Volume 34 Issue 1, October 2015
Volume 33 Issue 4, May 2015
Volume 33 Issue 3, March 2015
Volume 33 Issue 2, February 2015
Volume 33 Issue 1, March 2015 Special Issue on Contextual Search and Recommendation

2014
Volume 32 Issue 4, October 2014
Volume 32 Issue 3, June 2014
Volume 32 Issue 2, April 2014
Volume 32 Issue 1, January 2014

2013
Volume 31 Issue 4, November 2013
Volume 31 Issue 3, July 2013
Volume 31 Issue 2, May 2013
Volume 31 Issue 1, January 2013

2012
Volume 30 Issue 4, November 2012
Volume 30 Issue 3, August 2012
Volume 30 Issue 2, May 2012
Volume 30 Issue 1, February 2012

2011
Volume 29 Issue 4, December 2011
Volume 29 Issue 3, July 2011
Volume 29 Issue 2, April 2011

2010
Volume 29 Issue 1, December 2010
Volume 28 Issue 4, November 2010
Volume 28 Issue 3, June 2010
Volume 28 Issue 2, May 2010
Volume 28 Issue 1, January 2010

2009
Volume 27 Issue 4, November 2009
Volume 27 Issue 3, May 2009
Volume 27 Issue 2, February 2009

2008
Volume 27 Issue 1, December 2008
Volume 26 Issue 4, September 2008
Volume 26 Issue 3, June 2008
Volume 26 Issue 2, March 2008

2007
Volume 26 Issue 1, November 2007
Volume 25 Issue 4, October 2007
Volume 25 Issue 3, July 2007
Volume 25 Issue 2, April 2007
Volume 25 Issue 1, February 2007

2006
Volume 24 Issue 4, October 2006
Volume 24 Issue 3, July 2006
Volume 24 Issue 2, April 2006
Volume 24 Issue 1, January 2006

2005
Volume 23 Issue 4, October 2005
Volume 23 Issue 3, July 2005
Volume 23 Issue 2, April 2005
Volume 23 Issue 1, January 2005

2004
Volume 22 Issue 4, October 2004
Volume 22 Issue 3, July 2004
Volume 22 Issue 2, April 2004
Volume 22 Issue 1, January 2004

2003
Volume 21 Issue 4, October 2003
Volume 21 Issue 3, July 2003
Volume 21 Issue 2, April 2003
Volume 21 Issue 1, January 2003

2002
Volume 20 Issue 4, October 2002
Volume 20 Issue 3, July 2002
Volume 20 Issue 2, April 2002
Volume 20 Issue 1, January 2002

2001
Volume 19 Issue 4, October 2001
Volume 19 Issue 3, July 2001
Volume 19 Issue 2, April 2001
Volume 19 Issue 1, Jan. 2001

2000
Volume 18 Issue 4, Oct. 2000
Volume 18 Issue 3, July 2000
Volume 18 Issue 2, April 2000
Volume 18 Issue 1, Jan. 2000

1999
Volume 17 Issue 4, Oct. 1999
Volume 17 Issue 3, July 1999
Volume 17 Issue 2, April 1999
Volume 17 Issue 1, Jan. 1999

1998
Volume 16 Issue 4, Oct. 1998
Volume 16 Issue 3, July 1998
Volume 16 Issue 2, April 1998
Volume 16 Issue 1, Jan. 1998

1997
Volume 15 Issue 4, Oct. 1997
Volume 15 Issue 3, July 1997
Volume 15 Issue 2, April 1997
Volume 15 Issue 1, Jan. 1997

1996
Volume 14 Issue 4, Oct. 1996
Volume 14 Issue 3, July 1996
Volume 14 Issue 2, April 1996
Volume 14 Issue 1, Jan. 1996

1995
Volume 13 Issue 4, Oct. 1995 Special issue on video information retrieval
Volume 13 Issue 3, July 1995
Volume 13 Issue 2, April 1995
Volume 13 Issue 1, Jan. 1995

1994
Volume 12 Issue 4, Oct. 1994
Volume 12 Issue 3, July 1994
Volume 12 Issue 2, April 1994 Special issue on social science perspectives on IS
Volume 12 Issue 1, Jan. 1994

1993
Volume 11 Issue 4, Oct. 1993
Volume 11 Issue 3, July 1993
Volume 11 Issue 2, April 1993
Volume 11 Issue 1, Jan. 1993

1992
Volume 10 Issue 4, Oct. 1992 Special issue on user interface software and technology
Volume 10 Issue 3, July 1992
Volume 10 Issue 2, April 1992
Volume 10 Issue 1, Jan. 1992

1991
Volume 9 Issue 4, Oct. 1991
Volume 9 Issue 3, July 1991 Special issue on research and development in information retrieval
Volume 9 Issue 2, April 1991 Special issue on computer—human interaction
Volume 9 Issue 1, Jan. 1991

1990
Volume 8 Issue 4, Oct. 1990
Volume 8 Issue 3, July 1990
Volume 8 Issue 2, Apr. 1990
Volume 8 Issue 1, Jan. 1990

1989
Volume 7 Issue 4, Oct. 1989
Volume 7 Issue 3, July 1989
Volume 7 Issue 2, April 1989
Volume 7 Issue 1, Jan. 1989

1988
Volume 6 Issue 4, Oct. 1988
Volume 6 Issue 3, July 1988
Volume 6 Issue 2, April 1988
Volume 6 Issue 1, Jan. 1988

1987
Volume 5 Issue 4, Oct. 1987
Volume 5 Issue 3, July 1987
Volume 5 Issue 2, April 1987
Volume 5 Issue 1, Jan. 1987

1986
Volume 4 Issue 4, Oct. 1986
Volume 4 Issue 3, July 1986 Special issue: selected papers from the conference on office information systems
Volume 4 Issue 2, April 1986
Volume 4 Issue 1, Jan. 1986

1985
Volume 3 Issue 4, Oct. 1985
Volume 3 Issue 3, July 1985
Volume 3 Issue 2, April 1985
Volume 3 Issue 1, Jan. 1985

1984
Volume 2 Issue 4, Oct. 1984
Volume 2 Issue 3, July 1984
Volume 2 Issue 2, April 1984
Volume 2 Issue 1, Jan. 1984

1983
Volume 1 Issue 4, Oct. 1983
Volume 1 Issue 3, July 1983
Volume 1 Issue 2, April 1983
Volume 1 Issue 1, Jan. 1983
 
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