Adelaide Research & Scholarship
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https://hdl.handle.net/2440/87411
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| Type: | Conference paper |
| Title: | Categorizing and ranking search engine's results by semantic similarity |
| Author: | Hao, T. Lu, Z. Wang, S. Zou, T. Gu, S. Wenyin, L. |
| Citation: | Proceedings of the 2nd International Conference on Ubiquitous Information Management and Communication, ICUIMC 2008, 2008, pp.284-288 |
| Publisher: | ACM |
| Issue Date: | 2008 |
| ISBN: | 9781595939937 |
| Conference Name: | 2nd International Conference on Ubiquitous Information Management and Communication (ICUIMC 2008) (21 Feb 2008 - 1 Feb 2008 : Seoul, Korea) |
| Statement of Responsibility: | Tianyong Hao, Zhi Lu, Shitong Wang, Tiansong Zou, Shenhua Gu, Liu Wenyin |
| Abstract: | An automatic method for text categorizing and ranking search engine's results by semantic similarity is proposed in this paper. We first obtain nouns and verbs from snippets obtained from search engine using Name Entity Recognition and part-of speech. A semantic similarity algorithm based on WordNet is proposed to calculate the similarity of each snippet to each of the pre-defined categories. A balanced similarity ranking method combined with Google's rank and timeliness of the pages is proposed to rank these snippets. Preliminary experiments with 500 labeled questions from TREC03 show that 72.7% are correctly categorized. |
| Keywords: | Semantic similarity categorizing ranking search engine |
| Rights: | Copyright status unknown |
| DOI: | 10.1145/1352793.1352854 |
| Published version: | http://dx.doi.org/10.1145/1352793.1352854 |
| Appears in Collections: | Aurora harvest 2 Computer Science publications |
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