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» Using Information Extraction to Improve Document Retrieval
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NLDB
2007
Springer
15 years 10 months ago
Text Segmentation Based on Document Understanding for Information Retrieval
Information retrieval needs to match relevant texts with a given query. Selecting appropriate parts is useful when documents are long, and only portions are interesting to the user...
Violaine Prince, Alexandre Labadié
CORR
1999
Springer
120views Education» more  CORR 1999»
15 years 4 months ago
Cross-Language Information Retrieval for Technical Documents
This paper proposes a Japanese/English crosslanguage information retrieval (CLIR) system targeting technical documents. Our system first translates a given query containing techni...
Atsushi Fujii, Tetsuya Ishikawa
136
Voted
ICMCS
2006
IEEE
124views Multimedia» more  ICMCS 2006»
15 years 10 months ago
Combining Textual and Visual Ontologies to Solve Medical Multimodal Queries
In order to solve medical multimodal queries, we propose to split the queries in different dimensions using ontology. We extract both textual and visual terms depending on the ont...
Saïd Radhouani, Joo-Hwee Lim, Jean-Pierre Che...
151
Voted
AINA
2010
IEEE
15 years 9 months ago
Extracting Named Entities and Synonyms from Wikipedia
—In many search domains, both contents and searches are frequently tied to named entities such as a person, a company or similar. An example of such a domain is a news archive. O...
Christian Bohn, Kjetil Nørvåg
139
Voted
KDD
2004
ACM
163views Data Mining» more  KDD 2004»
16 years 5 months ago
Exploiting dictionaries in named entity extraction: combining semi-Markov extraction processes and data integration methods
We consider the problem of improving named entity recognition (NER) systems by using external dictionaries--more specifically, the problem of extending state-of-the-art NER system...
William W. Cohen, Sunita Sarawagi