System and method for automatically establishing city shop information library based on video analysis, searching and aggregation

Abstract

The invention discloses a system and method for automatically establishing a city shop information library based on video analysis, searching and aggregation. The system comprises an automatic merchant information and group buying information searching and aggregating unit, a unit for establishing an ontology knowledge base of merchant types, a unit for obtaining merchant information to be classified, a unit for establishing a merchant information correcting word bank and correcting information and an automatic merchant information classifying unit. The automatic merchant information and group buying information searching and aggregating unit is used for searching and aggregating merchant information. The unit for establishing the ontology knowledge base of the merchant types is used for classifying unclassified merchant information. The unit for obtaining the merchant information to be classified is used for obtaining the merchant information to be classified in a wide range. The unit for establishing the merchant information correcting word bank and correcting the information is used for correcting the merchant information which is identified to be incorrect. The automatic merchant information classifying unit is used for automatically obtaining the correct type of the merchant information. By the adoption of the system and method for automatically establishing the city shop information library based on video analysis, searching and aggregation, execution is more convenient and more efficient, and information is more accurate.

Description

technical field [0001] The invention relates to an automatic construction system of city store information database based on video analysis and search aggregation, which belongs to the technical field of Internet and image recognition. Background technique [0002] At present, various business websites and group buying websites on the Internet have a large amount of information, and the types are also intricate. There is no unified classification standard. Consumers want to find the goods they need without knowing what category it belongs to. For example, there are as many as 9 categories of products on Dianping.com, and as many as 8 types of products on Meituan.com. The classification standards of each website are different, so that products will be placed in different categories of web pages. Consumers often need to open another website after clicking this website to find the webpage where their products are located. It often takes dozens or even dozens of clicks. However,...

AI Technical Summary

Problems solved by technology

[0003] Searching and aggregating a large number of business group buying websites will inevitably generate a large number of business information. For a large number of business information, we need to know the category to which each piece of information belongs. If we manually classify one by one, this will be a huge project. Unrealistic, if we have our own city business information database, this will have a multiplier effect, and there is no relevant report yet

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