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» A Hidden Markov Model Information Retrieval System
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AAAI
2004
15 years 8 months ago
Interactive Information Extraction with Constrained Conditional Random Fields
Information Extraction methods can be used to automatically "fill-in" database forms from unstructured data such as Web documents or email. State-of-the-art methods have...
Trausti T. Kristjansson, Aron Culotta, Paul A. Vio...
WSDM
2009
ACM
188views Data Mining» more  WSDM 2009»
16 years 1 months ago
Is Wikipedia link structure different?
In this paper, we investigate the difference between Wikipedia and Web link structure with respect to their value as indicators of the relevance of a page for a given topic of re...
Jaap Kamps, Marijn Koolen
CIKM
2010
Springer
15 years 5 months ago
Rank learning for factoid question answering with linguistic and semantic constraints
This work presents a general rank-learning framework for passage ranking within Question Answering (QA) systems using linguistic and semantic features. The framework enables query...
Matthew W. Bilotti, Jonathan L. Elsas, Jaime G. Ca...
WWW
2005
ACM
16 years 7 months ago
Finding the search engine that works for you
A search engine evaluation model that considers over seventy performance and feature parameters is presented. The design of a web-based system that allows the user to tailor the m...
Kin F. Li, Wei Yu, Shojiro Nishio, Yali Wang
SIGIR
2008
ACM
15 years 7 months ago
A few examples go a long way: constructing query models from elaborate query formulations
We address a specific enterprise document search scenario, where the information need is expressed in an elaborate manner. In our scenario, information needs are expressed using a...
Krisztian Balog, Wouter Weerkamp, Maarten de Rijke