Research of vertical search engine index module for college entrance examination Forum

DOI

10.2991/gcmce-17.2017.6How to use a DOI?

Keywords

Vertical search engine, Classification system, Classification index.

Abstract

The vertical search engine index classification method based on ontology, through the introduction of text classification in PubMed forum based on ontology semantic information is added into index, can effectively improve the vertical search engine retrieval recall and precision, improve the relevance of search results ranking results. Firstly, the design of a classification system based on domain ontology, achieve fine-grained multi class text classification; and then design a new classification index structure, the categories of information and information and the formation of effective combination of keywords, classification index; finally the generating algorithm of classification index design, and puts forward the classification index compression, optimization method.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Yangyang Guo
AU  - Cao Hui
AU  - Fucheng Wan
PY  - 2017/06
DA  - 2017/06
TI  - Research of vertical search engine index module for college entrance examination Forum
BT  - Proceedings of the 2017 Global Conference on Mechanics and Civil Engineering (GCMCE 2017)
PB  - Atlantis Press
SP  - 27
EP  - 30
SN  - 2352-5401
UR  - https://doi.org/10.2991/gcmce-17.2017.6
DO  - 10.2991/gcmce-17.2017.6
ID  - Guo2017/06
ER  -