What is parallel search technology

What is parallel search technology

Parallel search engine (also known as integrated search engine, meta search engine, large search engine) is a search tool that can search multiple search engines at the same time and return the search results with a unified search interface. Its structural model is shown in Figure 1. . Metacrawler is the world's first parallel search engine. It uses several top search engines (Google, hoo, About, etc.) to perform parallel searches and returns the most relevant search results, making web page retrieval easier. Through its conversion function, the parallel search engine converts the search terms into a form acceptable to the search engine and submits them to the search engine for finding matching records, deduplicating records, and integrating search results. Since the parallel search engine can collaboratively retrieve multiple search engines, ignore the structural differences of its data sources, eliminate duplicate records between each other, and check the validity of the retrieval result information, so high-quality retrieval results can be obtained.

Figure 1 The basic structural model of parallel search engines Compared with independent search engines, parallel search engines have four advantages:
(1) Retrieve information to expand the coverage of the Internet. Studies have shown that Internet data growth is much faster than the speed of independent engines indexing network data, leading to the gradual decline in the coverage of Internet by mainstream independent search engines, and parallel search engines can alleviate this contradiction.
(2) Improve the scalability of information retrieval. Using parallel search engines to retrieve network information is easier to expand than using centralized independent search engines.
(3) Parallel search can use multiple search engines simultaneously. Users only need to submit a query once to use multiple independent engines, without having to be familiar with the retrieval interface of each independent engine, and parallel search engines can sort and redundantly retrieve results.
(4) Improve search efficiency. Sometimes the retrieval speed of parallel search is lower than that of a single independent search engine, but parallel search can obtain a larger result set and provide users with more effective retrieval information. Some scholars believe that the future web search service will be provided by many professional engines that cover a small part of the Internet. The task of the general large-scale retrieval system will be replaced by a parallel search engine. Compared with some mature independent search engines, parallel search engines still have shortcomings. Since the parallel search engine basically has no search information managed by itself, it cannot obtain the description information of the search information, and its search quality also depends in part on the independent search engine that provides services for it.
(1) The parallel search engine may not support some advanced search functions, such as advanced Boolean search.
(2) The parallel search engine does not return all search results. For example, it only returns the most relevant search results of each search engine to the user. If an independent search engine does not respond within a specified time, the search results are ignored .
(3) Because duplicate records generally appear between independent search engines, parallel search engines must face the problem of information redundancy. Literature [4] proposed Agent-based methods, including natural language analyzer, query customization, web page retrieval, web page filtering, web page sorting and user option Agent to solve the above problems. This article is based on grid-based parallel search engine, and the idea of ​​reference is to solve some problems of parallel search engine.

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