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AICCSA
2008
IEEE
245views Hardware» more  AICCSA 2008»
15 years 11 months ago
Rapid and robust ranking of text documents in a dynamically changing corpus
Ranking documents in a selected corpus plays an important role in information retrieval systems. Despite notable advances in this direction, with continuously accumulating text do...
Byung-Hoon Park, Nagiza F. Samatova, Rajesh Munava...
JCST
2008
138views more  JCST 2008»
15 years 4 months ago
Predicting Chinese Abbreviations from Definitions: An Empirical Learning Approach Using Support Vector Regression
In Chinese, phrases and named entities play a central role in information retrieval. Abbreviations, however, make keyword-based approaches less effective. This paper presents an em...
Xu Sun, Houfeng Wang, Bo Wang 0003
IR
2011
14 years 11 months ago
Learning to rank for why-question answering
In this paper, we evaluate a number of machine learning techniques for the task of ranking answers to why-questions. We use TF-IDF together with a set of 36 linguistically motivate...
Suzan Verberne, Hans van Halteren, Daphne Theijsse...
ACL
2012
13 years 7 months ago
Modeling Sentences in the Latent Space
Sentence Similarity is the process of computing a similarity score between two sentences. Previous sentence similarity work finds that latent semantics approaches to the problem ...
Weiwei Guo, Mona T. Diab
ICTIR
2009
Springer
15 years 2 months ago
An Analysis of NP-Completeness in Novelty and Diversity Ranking
Abstract. A useful ability for search engines is to be able to rank objects with novelty and diversity: the top k documents retrieved should cover possible interpretations of a que...
Ben Carterette