Liu, G.Z.: Semantic vector space model : implementation and evaluation (1997)
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- Abstract
- 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. Both document and queries are represented as semantic matrices. A search mechanism is designed to compute the similarity between 2 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 tagged as the pre-processor of the indexing. The prototype system was used in an experimental study to evaluate this technique in terms of precision, recall, and effectiveness of relevance ranking. Results show that if documents and queries were too short, the technique was less effective than VSM. But with longer documents and queires, especially when original docuemtns were used as queries, the system based on this technique was found be performance better than SMART
