1997 SemanticVectorSpaceModel
- (Liu, 1997) ⇒ Geoffrey Z. Liu. (1997). “Semantic Vector Space Model: Implementation and Evaluation.” In: Journal of the American Society for Information Science, 48(5).
Subject Headings: Relation Recognition, Semantic Vector Space Model.
Notes
Cited By
- (Khoo, 1997)
- Finally, Liu (1997) have investigated what I call partial relation matching. Instead of trying to match the whole concept-relation-concept triple (i.e. both concepts as well as the relation between them), he sought to match individual concepts together with the semantic role that the concept has in the sentence. In other words, instead of trying to find matches for "term1 ->(relation)-> term2", his system sought to find matches for "term1 ->(relation)" and "(relation)-> term2" separatelly, Liu used case roles and the vector-space retrieval model, and was able to obtain positive results only for long queries (abstracts that are used as queries).
Quotes
=Author Keywords
Computational Linguistics; Information Technology; Natural Language Processing Systems; Theorem Proving; Heuristic Methods
Abstract
This article presents the Semantic Vector Space Model (SVSM), a text representation and searching technique based on the combination of Vector Space Model (VSM) with heuristic syntax parsing and distributed representation of semantic case structures. In this model, both documents and queries are represented as semantic matrices. A search mechanism is designed to compute the similarity between two semantic matrices to predict relevancy. A prototype system was built to implement this model by modifying the SMART system and using the Xerox Part-Of-Speech (P-O-S) tagger as the pre-processor of the indexing process. The prototype system was used in an experimental study to evaluate this technique in terms of precision, recall, and effectiveness of relevance ranking. The results of the study showed that if documents and queries were too short (typically2 lines in length), the technique was less effective than VSM. But with longer documents and queries, especially when original documents were used as queries, we found that the system based on our technique had significantly better performance than SMART.
References
,
| Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
|---|---|---|---|---|---|---|---|---|---|---|
| 1997 SemanticVectorSpaceModel | Geoffrey Z. Liu | Semantic Vector Space Model: Implementation and Evaluation | Journal of the American Society for Information Science | 1997 |