Name
Title | ||
|---|---|---|
Minimally-supervised extraction of domain-specific part-whole relations using Wikipedia as knowledge-base |
Abstract | ||
|---|---|---|
We present a minimally-supervised approach for learning part-whole relations from texts. Unlike previous techniques, we focused on sparse, domain-specific texts. The novelty in our approach lies in the use of Wikipedia as a knowledge-base, from which we first acquire a set of reliable patterns that express part-whole relations. This is achieved by a minimally-supervised algorithm. We then use the patterns acquired to extract part-whole relation triples from a collection of sparse, domain-specific texts. Our strategy, of learning in one domain and applying the knowledge in another domain is based upon the notion of domain-adaption. It allows us to overcome the challenges of learning the relations directly from the sparse, domain-specific corpus. Our experimental evaluations reveal that, despite its general-purpose nature, Wikipedia can be exploited as a source of knowledge for improving the performance of domain-specific part-whole relation extraction. As our other contributions, we propose a mechanism that mitigates the negative impact of semantic-drift on minimally-supervised algorithms. Also, we represent the patterns in the extracted relations using sophisticated syntactic structures that avoid the limitations of traditional surface string representations. In addition, we show that domain-specific part-whole relations cannot be conclusively classified in existing taxonomies. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.datak.2012.06.004 | Data Knowl. Eng. |
Keywords | Field | DocType |
part-whole relation,domain-specific text,domain-specific corpus,experimental evaluation,domain-specific part-whole relation extraction,minimally-supervised algorithm,minimally-supervised extraction,minimally-supervised approach,part-whole relation triple,domain-specific part-whole relation,general-purpose nature,text mining,relation extraction | Data mining,Text mining,Information retrieval,Computer science,Natural language processing,Artificial intelligence,Novelty,Knowledge base,Syntax,Ontology learning,Database,Relationship extraction | Journal |
Volume | Issue | ISSN |
85, | 1 | 0169-023X |
Citations | PageRank | References |
16 | 0.69 | 36 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ashwin Ittoo | 1 | 61 | 6.58 |
| Gosse Bouma | 2 | 483 | 70.88 |