Efficient Term Extraction and Indexing Approach in Small-Scale Web Search of Uyghur Language

In order to avoid the frequently read-write of hard disk and to speed up the search, the index should be saving in the memory in the small-scale web search. But, to express the original information by fewer memory spaces, also needs for index compression, and this would increases the computation expenses or brings certain harm to the original information in a way. In this research of Uyghur small-scale web search, in order to speed up the retrieval and query speed, inverted index has established uses Hash table data structure and entirely stay resident in memory. In the aspect of index compression, have not uses any compression technique, but proposed a word grouping approach based on simplified N-gram statistical model ,and extracting semantic words that structurally stable, semantically complete and independent ,and greatly reduces the scale of indexing item list. Thereby, not only served the purpose of index compression, but also solved the ambiguity problem certain extent and improved the search precision obviously. The experimental result indicated that, our method is feasible and effective.