Information Systems (TOIS)


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ACM Transactions on Information Systems (TOIS), Volume 31 Issue 1, January 2013

Enriching Documents with Examples: A Corpus Mining Approach
Jinhan Kim, Sanghoon Lee, Seung-Won Hwang, Sunghun Kim
Article No.: 1
DOI: 10.1145/2414782.2414783

Software developers increasingly rely on information from the Web, such as documents or code examples on application programming interfaces (APIs), to facilitate their development processes. However, API documents often do not include enough...

Approximate Recall Confidence Intervals
William Webber
Article No.: 2
DOI: 10.1145/2414782.2414784

Recall, the proportion of relevant documents retrieved, is an important measure of effectiveness in information retrieval, particularly in the legal, patent, and medical domains. Where document sets are too large for exhaustive relevance...

X-Class: Associative Classification of XML Documents by Structure
Gianni Costa, Riccardo Ortale, Ettore Ritacco
Article No.: 3
DOI: 10.1145/2414782.2414785

The supervised classification of XML documents by structure involves learning predictive models in which certain structural regularities discriminate the individual document classes. Hitherto, research has focused on the adoption of prespecified...

The Effect of Social and Physical Detachment on Information Need
Elad Yom-Tov, Fernando Diaz
Article No.: 4
DOI: 10.1145/2414782.2414786

The information need of users and the documents which answer this need are frequently contingent on the different characteristics of users. This is especially evident during natural disasters, such as earthquakes and violent weather incidents,...

Regularized Latent Semantic Indexing: A New Approach to Large-Scale Topic Modeling
Quan Wang, Jun Xu, Hang Li, Nick Craswell
Article No.: 5
DOI: 10.1145/2414782.2414787

Topic modeling provides a powerful way to analyze the content of a collection of documents. It has become a popular tool in many research areas, such as text mining, information retrieval, natural language processing, and other related fields. In...