Document summarization plays an increasingly important role with the exponential growth of documents on the Web. Many supervised and unsupervised approaches have been proposed to ...
Liangda Li, Ke Zhou, Gui-Rong Xue, Hongyuan Zha, Y...
Retrieval systems rank documents according to their retrieval status values (RSV) if these are monotonously increasing with the probability of relevance of documents. In this work,...
The full integration of information retrieval (IR) features into a database management system (DBMS) has long been recognized as both a significant goal and a challenging undertak...
Samuel DeFazio, Amjad M. Daoud, Lisa Ann Smith, Ja...
Traditional machine-learned ranking algorithms for web search are trained in batch mode, which assume static relevance of documents for a given query. Although such a batch-learni...
Term-weighting functions derived from various models of retrieval aim to model human notions of relevance more accurately. However, there is a lack of analysis of the sources of e...