Dictionary-based text categorization of chemical web pages
文献类型：期刊论文
| 作者 | Liang, CY; Guo, L; Xia, ZH; Nie, FG; Li, XX; Su, LA; Yang, ZY |
| 刊名 | INFORMATION PROCESSING & MANAGEMENT
 |
| 出版日期 | 2006-07-01 |
| 卷号 | 42期号:4页码:1017-1029 |
| 关键词 | chemistry-focused search engine dictionary-based text categorization automatic segmentation k-NN latent semantic indexing voting |
| ISSN号 | 0306-4573 |
| 其他题名 | Inf. Process. Manage. |
| 中文摘要 | A new dictionary-based text categorization approach is proposed to classify the chemical web pages efficiently. Using a chemistry dictionary, the approach can extract chemistry-related information more exactly from web pages. After automatic segmentation on the documents to find dictionary terms for document expansion, the approach adopts latent semantic indexing (LSI) to produce the final document vectors, and the relevant categories are finally assigned to the test document by using the k-NN text categorization algorithm. The effects of the characteristics of chemistry dictionary and test collection on the categorization efficiency are discussed in this paper, and a new voting method is also introduced to improve the categorization performance further based on the collection characteristics. The experimental results show that the proposed approach has the superior performance to the traditional categorization method and is applicable to the classification of chemical web pages. (c) 2005 Elsevier Ltd. All rights reserved. |
| 英文摘要 | A new dictionary-based text categorization approach is proposed to classify the chemical web pages efficiently. Using a chemistry dictionary, the approach can extract chemistry-related information more exactly from web pages. After automatic segmentation on the documents to find dictionary terms for document expansion, the approach adopts latent semantic indexing (LSI) to produce the final document vectors, and the relevant categories are finally assigned to the test document by using the k-NN text categorization algorithm. The effects of the characteristics of chemistry dictionary and test collection on the categorization efficiency are discussed in this paper, and a new voting method is also introduced to improve the categorization performance further based on the collection characteristics. The experimental results show that the proposed approach has the superior performance to the traditional categorization method and is applicable to the classification of chemical web pages. (c) 2005 Elsevier Ltd. All rights reserved. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Information Systems ; Information Science & Library Science |
| 研究领域[WOS] | Computer Science ; Information Science & Library Science |
| 关键词[WOS] | INFORMATION-RETRIEVAL |
| 收录类别 | SCI ; SSCI |
| 原文出处 | |
| 语种 | 英语 |
| WOS记录号 | WOS:000236006600010 |
| 公开日期 | 2013-10-24 |
| 版本 | 出版稿 |
| 源URL | [http://ir.ipe.ac.cn/handle/122111/3948]  |
| 专题 | 过程工程研究所_研究所（批量导入） |
| 作者单位 | Chinese Acad Sci, Inst Proc Engn, Key Lab Multiphase React, Beijing 100080, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liang, CY,Guo, L,Xia, ZH,et al. Dictionary-based text categorization of chemical web pages[J]. INFORMATION PROCESSING & MANAGEMENT,2006,42(4):1017-1029. |
| APA | Liang, CY.,Guo, L.,Xia, ZH.,Nie, FG.,Li, XX.,...&Yang, ZY.(2006).Dictionary-based text categorization of chemical web pages.INFORMATION PROCESSING & MANAGEMENT,42(4),1017-1029. |
| MLA | Liang, CY,et al."Dictionary-based text categorization of chemical web pages".INFORMATION PROCESSING & MANAGEMENT 42.4(2006):1017-1029. |
入库方式： OAI收割
来源：过程工程研究所
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