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信息检索技术的比较：潜在语义索引（LSI）和概念索引（CI）Comparison of information retrieval techniques: Latent semantic indexing (LSI) and Concept indexing (CI) |
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| 课程网址: | http://videolectures.net/solomon_dobsa_lsici/ |
| 主讲教师: | Jasminka Dobsa |
| 开课单位: | 萨格勒布大学 |
| 开课时间: | 2007-02-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Information retrieval in the vector space model is based on literal matching of terms in the documents and the queries. The model is implemented by creating the term-document matrix, which is formed on the base of frequencies of terms in documents. Literal matching of terms does not necessarily retrieve all relevant documents. Synonymy (multiple words having the same meaning) and polysemy (words having multiple meaning) are two major obstacles for efficient information retrieval. Latent semantic indexing (LSI) and concept indexing (CI) are information retrieval techniques embedded in the vector space model, which address the problem of synonymy and polysemy. The method of LSI is an information retrieval technique using a low-rank singular value decomposition (SVD) of the term-document matrix. Although the LSI method has empirical success, it suffers from the lack of interpretation for the low-rank approximation and, consequently, the lack of controls for accomplishing specific tasks in information retrieval. The method of CI uses centroids of clusters or so-called concept decomposition (CD) for lowering the rank of the term-document matrix. Here we compare SVD/LSI and CD/CI in terms of matrix approximations and precision of information retrieval. |
| 关 键 词: | 向量空间; 文字匹配; 术语文档矩阵 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-09-21：cwx |
| 阅读次数: | 92 |