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ACM Transactions on Information Systems (TOIS), Volume 35 Issue 3, June 2017

Time-Aware Click Model
Yiqun Liu, Xiaohui Xie, Chao Wang, Jian-Yun Nie, Min Zhang, Shaoping Ma
Article No.: 16
DOI: 10.1145/2988230

Click-through information is considered as a valuable source of users’ implicit relevance feedback for commercial search engines. As existing studies have shown that the search result position in a search engine result page (SERP) has a very...

Hilbert Exclusion: Improved Metric Search through Finite Isometric Embeddings
Richard Connor, Franco Alberto Cardillo, Lucia Vadicamo, Fausto Rabitti
Article No.: 17
DOI: 10.1145/3001583

Most research into similarity search in metric spaces relies on the triangle inequality property. This property allows the space to be arranged according to relative distances to avoid searching some subspaces. We show that many common metric...

Cost-Effective Online Trending Topic Detection and Popularity Prediction in Microblogging
Zhongchen Miao, Kai Chen, Yi Fang, Jianhua He, Yi Zhou, Wenjun Zhang, Hongyuan Zha
Article No.: 18
DOI: 10.1145/3001833

Identifying topic trends on microblogging services such as Twitter and estimating those topics’ future popularity have great academic and business value, especially when the operations can be done in real time. For any third party, however,...

On Crowdsourcing Relevance Magnitudes for Information Retrieval Evaluation
Eddy Maddalena, Stefano Mizzaro, Falk Scholer, Andrew Turpin
Article No.: 19
DOI: 10.1145/3002172

Magnitude estimation is a psychophysical scaling technique for the measurement of sensation, where observers assign numbers to stimuli in response to their perceived intensity. We investigate the use of magnitude estimation for judging the...

Targeted Advertising in Public Transportation Systems with Quantitative Evaluation
Dongxiang Zhang, Long Guo, Liqiang Nie, Jie Shao, Sai Wu, Heng Tao Shen
Article No.: 20
DOI: 10.1145/3003725

In spite of vast business potential, targeted advertising in public transportation systems is a grossly unexplored research area. For instance, SBS Transit in Singapore can reach 1 billion passengers per year but the annual advertising revenue...

Re-Finding Behaviour in Vertical Domains
Seyedeh Sargol Sadeghi, Roi Blanco, Peter Mika, Mark Sanderson, Falk Scholer, David Vallet
Article No.: 21
DOI: 10.1145/2975590

Re-finding is the process of searching for information that a user has previously encountered and is a common activity carried out with information retrieval systems. In this work, we investigate re-finding in the context of vertical search,...

Inverted Treaps
Roberto Konow, Gonzalo Navarro, Charles L. A. Clarke, Alejandro López-Ortíz
Article No.: 22
DOI: 10.1145/3007186

We introduce a new representation of the inverted index that performs faster ranked unions and intersections while using similar space. Our index is based on the treap data structure, which allows us to intersect/merge the document identifiers...

Search Result Prefetching on Desktop and Mobile
Ryen W. White, Fernando Diaz, Qi Guo
Article No.: 23
DOI: 10.1145/3015466

Search result examination is an important part of searching. High page load latency for landing pages (clicked search results) can reduce the efficiency of the search process. Proactively prefetching landing pages in advance of clickthrough can...

Incorporating User Expectations and Behavior into the Measurement of Search Effectiveness
Alistair Moffat, Peter Bailey, Falk Scholer, Paul Thomas
Article No.: 24
DOI: 10.1145/3052768

Information retrieval systems aim to help users satisfy information needs. We argue that the goal of the person using the system, and the pattern of behavior that they exhibit as they proceed to attain that goal, should be incorporated into the...

Improving the Quality of Recommendations for Users and Items in the Tail of Distribution
Liang Hu, Longbing Cao, Jian Cao, Zhiping Gu, Guandong Xu, Jie Wang
Article No.: 25
DOI: 10.1145/3052769

Short-head and long-tail distributed data are widely observed in the real world. The same is true of recommender systems (RSs), where a small number of popular items dominate the choices and feedback data while the rest only account for a small...

Encoding Syntactic Knowledge in Neural Networks for Sentiment Classification
Minlie Huang, Qiao Qian, Xiaoyan Zhu
Article No.: 26
DOI: 10.1145/3052770

Phrase/Sentence representation is one of the most important problems in natural language processing. Many neural network models such as Convolutional Neural Network (CNN), Recursive Neural Network (RNN), and Long Short-Term Memory (LSTM) have been...

Compact Indexing and Judicious Searching for Billion-Scale Microblog Retrieval
Dongxiang Zhang, Liqiang Nie, Huanbo Luan, Kian-Lee Tan, Tat-Seng Chua, Heng Tao Shen
Article No.: 27
DOI: 10.1145/3052771

In this article, we study the problem of efficient top-k disjunctive query processing in a huge microblog dataset. In terms of compact indexing, we categorize the keywords into rare terms and common terms based on inverse document frequency...

Processing Long Queries Against Short Text: Top-k Advertisement Matching in News Stream Applications
Dongxiang Zhang, Yuchen Li, Ju Fan, Lianli Gao, Fumin Shen, Heng Tao Shen
Article No.: 28
DOI: 10.1145/3052772

Many real applications in real-time news stream advertising call for efficient processing of long queries against short text. In such applications, dynamic news feeds are regarded as queries to match against an advertisement (ad) database for...