Method for extracting attribution and comment word with template based on internet

Abstract

The invention provides a method for extracting an attribution and a comment word with a template based on internet, which comprises the steps of: memorizing an attribute template aiming at a concept, the classification of which is manually labeled, by a machine readable dictionary; checking the evaluation index of a classification algorithm, selecting the maximum entropy, and ensuring a PMI value and an attribution word when training a classification model; extracting an original attribution set by collocating a template based on the internet, filtering the attribution based on a classification rule, expanding an attribution set with a connecting phrase template based on the assumption of Resnik, filtering again to form a process of cyclic iteration, evaluating the performance of the attribution extracting method according to the precision, the recall ratio and the comprehensive index F to obtain a relationship curve graph of the precision and the recall ratio; and extracting an individal comment word to the product attribution based on the product attribution extracted by the internet to form an effective attribution-evaluation pair, judging good evaluation and bad evaluation according to the word characteristic of an evaluation adjective in evaluation information, and generating a market feedback comprehensive value.

Description

technical field [0001] The invention relates to the field of information retrieval, in particular to a method for extracting concept attributes and comment words. Background technique [0002] In all surveys around the world, search engines are the most used services on the Internet after e-mail. Search engine services can become the most popular service because it solves the bottleneck problem of users quickly locating information on the vast Internet. However, it still takes a lot of energy and time for users to search for information in the traditional way. This traditional way is just a simple symbol processing. Computers are different from human brain thinking. Humans can directly understand the meaning of words and the ideas of articles, while machines and algorithms cannot. When people see the word apple, they know that it refers to the round, watery, and delicious food. However, search engines can't understand it emotionally, and they can't compare apples with "roun...

AI Technical Summary

Problems solved by technology

When people see the word apple, they know that it refers to the round, watery, and delicious food. However, search engines can't understand it emotionally, and they can't compare apples with "round" and "with water". Water's ", "very delicious things" are equivalent

Therefore, in the face of the massive amount of information on the Internet, it is really difficult to find the answer you want directly in the search engine.

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