Search text labeling method and device

Abstract

The invention provides a search text labeling method and device. The search text labeling method comprises the following steps of obtaining a candidate participle set of a text to be searched; reading preset information of words matched with each candidate participle in the candidate participle set from a semantic resource base; performing labeling on the candidate participles in the candidate participle set according to the preset information to obtain an initial labeling result; obtaining entity participles and / or proper noun participles in the initial labeling result; performing labeling on each entity participle and / or proper noun participle according to preset features to obtain a middle labeling result; generating a target labeling result according to a preset rule, association information of each candidate participle, the initial labeling result and the middle labeling result; labeling the search text according to the target labeling result, wherein the labeling result includes at least one target candidate participle and labeling information of each target candidate participle. By using the method and the device provided by the invention, the search text labeling precision can be effectively improved.

Description

technical field [0001] The invention relates to the field of communication technology, in particular to a method and device for marking search text. Background technique [0002] In the era of mobile search, with the shrinking of the mobile terminal operation interface and the increasing difficulty of users' traditional input, the search engine product model that relies on keyboard input and returns ten search results on one screen can no longer meet the needs of users. Voice and image-based input modes and more precise, aggregated, and recommended search results will become the "standard configuration" of a new generation of mobile search products. In related technologies, the process of lexical analysis is a serial mode divided according to tasks, that is, word segmentation, part-of-speech tagging, and proper name recognition are processed in stages, the granularity problem is solved in word segmentation, the part-of-speech problem is solved in part-of-speech tagging, and ...

AI Technical Summary

Problems solved by technology

[0003] In this way, because word segmentation, part-of-speech tagging, and proper name recognition are processed in stages, it is in a loosely coupled state, domain adaptation is difficult, and constraints are missing, errors are easy to accumulate, resulting in low accuracy of tagging effects

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