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Research and Development of Search Engine Based on Focus Relevance Ranking

Author: WenQuan
Tutor: DingXiangWu
School: Donghua University
Course: Computer Architecture
Keywords: Vertical search engine PageRank Focus Relevance Reptile theme User behavior model
CLC: TP391.3
Type: Master's thesis
Year: 2010
Downloads: 117
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Abstract


Search engines are an important tool for people to obtain useful information from the massive network data, the key elements of the research and application of network information. With the explosive growth of the network information as well as information on a wide range of development, quickly and efficiently is becoming more and more difficult to obtain the necessary information, general search engine can not meet the accuracy requirements of the users of information retrieval, professional The theme-oriented vertical search engine is becoming a hot research. The relevance sorting technology is one of the key technologies in the search engine, and the Get themes related data and query results set plays a vital role. The studied vertical search engine relevance technology, and analysis of one of the deficiencies of the Department, then the theme crawling based on the link structure sorted, based on the page right to re-sort and other proposed the improved models and algorithms, in order to improve the relevance ranking of the quality , thereby improving the performance of the vertical search engine. Final design to achieve a vertical search engine system. The main contribution of the paper include: (1) can not pass through the dark tunnel \the theme of data. (2) study the PageRank algorithm and its improved algorithm, by modeling the behavior of the user clicks on the Web, and to improve the link between the passing of PageRank values, which put forward the improved algorithm. Experimental results show that the algorithm is effective to avoid topic drift phenomenon occurred in the case of additional storage space. (3) for the web right to re-characterized extract excessive dimensions of the model defects, proposed heavy pages right to self-defined method defined in the web pages the right weight factors and separability criterion to measure the page right to re-factors of the right weight, which gives the page weight an evaluation function, effectively reducing the page feature space dimension. (4) integration of more than three improvement program proposed focus Relevance Sort program, and apply it to the implementation of the search engine. (5) use of Lucene text search engine framework, the car theme vertical search engine system resources. Practical application shows correlation between the vertical search engine focused relevance ranking, recall rate, have a different degree of precision to improve.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Retrieval machine
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