Nicola Ferro, Fabio Crestani, Marie-Francine Moens, Josiane's Advances in Information Retrieval: 38th European Conference PDF

By Nicola Ferro, Fabio Crestani, Marie-Francine Moens, Josiane Mothe, Fabrizio Silvestri, Giorgio Maria Di Nunzio, Claudia Hauff, Gianmaria Silvello

This e-book constitutes the refereed lawsuits of the thirty eighth eu convention on IR study, ECIR 2016, held in Padua, Italy, in March 2016.

The forty two complete papers and 28 poster papers offered including three keynote talks and six demonstration papers, have been conscientiously reviewed and chosen from 284 submissions. the quantity comprises the end result of four workshops in addition to four instructional papers additionally. Being the most suitable eu discussion board for the presentation of recent study leads to the sector of data Retrieval, ECIR contains a wide variety of subject matters corresponding to: social context and information, desktop studying, query answering, score, evaluate method, probalistic modeling, review matters, multimedia and collaborative filtering, and plenty of more.

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Extra info for Advances in Information Retrieval: 38th European Conference on IR Research, ECIR 2016, Padua, Italy, March 20-23, 2016. Proceedings

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Ali Montazeralghaem, Hamed Zamani, and Azadeh Shakery 729 735 741 748 754 Contents XXXVII An Empirical Comparison of Term Association and Knowledge Graphs for Query Expansion . . . . . . . . . . . . . . . . . . . . Saeid Balaneshinkordan and Alexander Kotov 761 Deep Learning to Predict Patient Future Diseases from the Electronic Health Records . . . . . . . . . . . . . . . . . . . . . . Riccardo Miotto, Li Li, and Joel T. Dudley 768 Improving Document Ranking for Long Queries with Nested Query Segmentation .

Mehedi Hasan, Alexander Kotov, Aravind Mohan, Shiyong Lu, and Paul M. Stieg Inferring the Socioeconomic Status of Social Media Users Based on Behaviour and Language . . . . . . . . . . . . . . . . . . . Vasileios Lampos, Nikolaos Aletras, Jens K. Geyti, Bin Zou, and Ingemar J. Cox Two Scrolls or One Click: A Cost Model for Browsing Search Results . . . Leif Azzopardi and Guido Zuccon 682 689 696 Determining the Optimal Session Interval for Transaction Log Analysis of an Online Library Catalogue.

For this reason, we expect that clustering results will be better if quotes are removed from the comments before computing similarity. To test this assumption we created two sets of training data. In the first set positive instances are comment pairs where the quote is left in the comments. In the second set positive instances are pairs of comments where we removed the shared quotes from the comments. For both training sets we set the topical similarity measure for each positive instance to be quoteScore = len(quoteC1 ) + len(quoteC2 )/2 ∗ len(sentence) (1) as the outcome.

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