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ACM Transactions on Information Systems (TOIS), Volume 34 Issue 1, October 2015

Identifying Opportunities for Valuable Encounters: Toward Context-Aware Social Matching Systems
Julia M. Mayer, Quentin Jones, Starr Roxanne Hiltz
Article No.: 1
DOI: 10.1145/2751557

Mobile social matching systems have the potential to transform the way we make new social ties, but only if we are able to overcome the many challenges that exist as to how systems can utilize contextual data to recommend interesting and relevant...

Latent Discriminative Models for Social Emotion Detection with Emotional Dependency
Xiaojun Quan, Qifan Wang, Ying Zhang, Luo Si, Liu Wenyin
Article No.: 2
DOI: 10.1145/2749459

Sentiment analysis of such opinionated online texts as reviews and comments has received increasingly close attention, yet most of the work is intended to deal with the detection of authors’ emotion. In contrast, this article presents our...

Deep Dependency Substructure-Based Learning for Multidocument Summarization
Su Yan, Xiaojun Wan
Article No.: 3
DOI: 10.1145/2766447

Most extractive style topic-focused multidocument summarization systems generate a summary by ranking textual units in multiple documents and extracting a proper subset of sentences biased to the given topic. Usually, the textual units are simply...

KNET: A General Framework for Learning Word Embedding Using Morphological Knowledge
Qing Cui, Bin Gao, Jiang Bian, Siyu Qiu, Hanjun Dai, Tie-Yan Liu
Article No.: 4
DOI: 10.1145/2797137

Neural network techniques are widely applied to obtain high-quality distributed representations of words (i.e., word embeddings) to address text mining, information retrieval, and natural language processing tasks. Most recent efforts have...

MWI-Sum: A Multilingual Summarizer Based on Frequent Weighted Itemsets
Elena Baralis, Luca Cagliero, Alessandro Fiori, Paolo Garza
Article No.: 5
DOI: 10.1145/2809786

Multidocument summarization addresses the selection of a compact subset of highly informative sentences, i.e., the summary, from a collection of textual documents. To perform sentence selection, two parallel strategies have been proposed: (a)...

A Document Retrieval Model Based on Digital Signal Filtering
Alberto Costa, Emanuele Di Buccio, Massimo Melucci
Article No.: 6
DOI: 10.1145/2809787

Information retrieval (IR) systems are designed, in general, to satisfy the information need of a user who expresses it by means of a query, by providing him with a subset of documents selected from a collection and ordered by decreasing relevance...