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- 614 creator feiyu-xu.
- 614 creator hans-uszkoreit.
- 614 creator hong-li.
- 614 creator niko-felger.
- 614 type InProceedings.
- 614 label "Adaptation of Relation Extraction Rules to New Domains".
- 614 sameAs 614.
- 614 abstract "This paper presents various strategies for improving the extraction performance of less prominent relations with the help of the rules learned for similar relations, for which large volumes of data are available that exhibit suitable data properties. The rules are learned via a minimally supervised machine learning system for relation extraction called DARE. Starting from semantic seeds, DARE extracts linguistic grammar rules associated with semantic roles from parsed news texts. The performance analysis with respect to different experiment domains shows that the data property plays an important role for DARE. Especially the redundancy of the data and the connectivity of instances and pattern rules have a strong influence on recall. However, most real-world data sets do not possess the desirable small-world property. Therefore, we propose three scenarios to overcome the data property problem of some domains by exploiting a similar domain with better data properties. The first two strategies stay with the same corpus but try to extract new similar relations with learned rules. The third strategy adapts the learned rules to a new corpus. All three strategies show that frequently mentioned relations can help in the detection of less frequent relations.".
- 614 hasAuthorList authorList.
- 614 hasTopic Linguistics.
- 614 isPartOf proceedings.
- 614 keyword "Information Extraction, Information Retrieval".
- 614 title "Adaptation of Relation Extraction Rules to New Domains".