A maximum entropy approach to named entity recognition
A maximum entropy approach to named entity recognition
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Automatic information extraction from large websites
Journal of the ACM (JACM)
ACM SIGKDD Explorations Newsletter
Learning surface text patterns for a Question Answering system
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Named entity recognition using an HMM-based chunk tagger
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Incorporating non-local information into information extraction systems by Gibbs sampling
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Locating complex named entities in web text
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A probabilistic model of redundancy in information extraction
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Unsupervised named-entity extraction from the Web: An experimental study
Artificial Intelligence
Ontology-driven information extraction with ontosyphon
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
Extracting relations in social networks from the web using similarity between collective contexts
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
A method for learning part-whole relations
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
Building a social network of research institutes from information available on the web
International Journal of Networking and Virtual Organisations
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We present a simple method to extract information from search engine snippets. Although the techniques presented are domain independent, this work focuses on extracting biographical information of historical persons from multiple unstructured sources on the Web. We first similarly find a list of persons and their periods of life by querying the periods and scanning the retrieved snippets for person names. Subsequently, we find biographical information for the persons extracted. In order to get insight in the mutual relations among the persons identified, we create a social network using co-occurrences on the Web. Although we use uncontrolled and unstructured Web sources, the information extracted is reliable. Moreover we show that Web Information Extraction can be used to create both informative and enjoyable applications.