Multi-dimension searching sequencing optimization algorithm and tool based on microblog data

Abstract

The invention discloses a multi-dimension searching sequencing optimization algorithm and tool based on microblog data. The algorithm optimizes original searching sequencing results of the Lucene on the aspects of three dimensions of data characteristics, user characteristics and application characteristics, and the optimized sequencing result is improved on the aspects of representing the data characteristics, according with the inquiry intention of a user, according with the application theme and the like. The multi-dimension searching sequencing optimization tool is achieved based on financial microblog data and is divided into three modules, and each module finishes the optimization in one dimension. A sequencing optimization module for the data characteristics achieves data characteristic optimization at the dimension I, a sequencing optimization module for the user characteristics achieves user characteristic optimization at the dimension II and comprises two sub-modules which are a searching label optimization sub-module and a searching log optimization sub-module, and a sequencing optimization module for the application characteristics achieves application characteristic optimization at the dimension III. The tool is suitable for optimizing all basic searching results of the Lucene, can achieve optimization sequencing of the original searching results of the Lucene in a system searching module, and provides better searching experience for the user.

Description

Technical field [0001] The invention relates to a multi-dimensional search and sort optimization algorithm, which optimizes Lucene search and sort results from the three dimensions of search data characteristics, search user characteristics and system application characteristics, and realizes a search optimization tool for a Web system based on financial microblog data . Background technique [0002] Social network data is becoming an important source of information for people, and Weibo data occupies a very important position in social data. Facing the massive amount of data on the Internet, it is necessary and important to use a data retrieval system for information retrieval. For certain keywords, the data retrieval system returns result data containing these keywords by searching the index. Generally, the data retrieval system uses certain formulas to calculate the correlation between the result data and the search keywords, and the higher correlation is returned to the user...

AI Technical Summary

Problems solved by technology

Obviously, a single word frequency position weighted retrieval sorting algorithm cannot meet the above requirements

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