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SIGIR
1998
ACM
13 years 11 months ago
Exploring the Similarity Space
Ranked queries are used to locate relevant documents in text databases. In a ranked query a list of terms is specified, then the documents that most closely match the query are re...
Justin Zobel, Alistair Moffat
SIGIR
1998
ACM
13 years 11 months ago
Real Life Information Retrieval: A Study of User Queries on the Web
Bernard J. Jansen, Amanda Spink, Judy Bateman, Tef...
SIGIR
1998
ACM
13 years 11 months ago
Hypertext Information Retrieval for the Web
The notion of searching a hypertext corpus has been around for some time, and is an especially important topic given the growth of the World Wide Web and the general dissatisfacti...
Eric W. Brown, Alan F. Smeaton
SIGIR
1998
ACM
14 years 3 months ago
Automatic Acquisition of Phrasal Knowledge for English-Chinese Bilingual Information Retrieval
Extraction of phrasal knowledge, such as proper names, domain-specific keyphrases and lexical templates from a domain-specific text collection are significant for developing effec...
Ming-Jer Lee, Lee-Feng Chien
SIGIR
1998
ACM
14 years 3 months ago
How Reliable Are the Results of Large-Scale Information Retrieval Experiments?
Two stages in measurement of techniques for information retrieval are gathering of documents for relevance assessment and use of the assessments to numerically evaluate effective...
Justin Zobel
SIGIR
1998
ACM
14 years 3 months ago
Web Document Clustering: A Feasibility Demonstration
Users of Web search engines are often forced to sift through the long ordered list of document “snippets” returned by the engines. The IR community has explored document cluste...
Oren Zamir, Oren Etzioni
SIGIR
1998
ACM
14 years 3 months ago
Advantages of Query Biased Summaries in Information Retrieval
1 This paper presents an investigation into the utility of document summarisation in the context of information retrieval, more specifically in the application of so called query b...
Anastasios Tombros, Mark Sanderson
SIGIR
1998
ACM
14 years 3 months ago
Boosting and Rocchio Applied to Text Filtering
We discuss two learning algorithms for text filtering: modified Rocchio and a boosting algorithm called AdaBoost. We show how both algorithms can be adapted to maximize any gene...
Robert E. Schapire, Yoram Singer, Amit Singhal