Method and device for determining suggest word
A technology of recommended words and candidate words, which is applied in the computer field, can solve the problems of large amount of calculations for recommended words and the inability to generate personalized recommended words for users, and achieve the effect of reducing workload and improving efficiency
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Embodiment 1
[0031] Embodiment 1 of the present application provides a method for determining recommended words, such as figure 1 As shown, the method includes the following steps:
[0032] Step 101: Receive a search request including query words sent by a user.
[0033] In this step, when a user wishes to perform an information search process, a search request including query words is actively initiated. The query words involved in this step may be the query words obtained by the user converting the item to be searched for, or the user actively selects the previously displayed recommended words as the new query words.
[0034] If the device for determining the recommended words (hereinafter referred to as the device for determining the recommended words) is a logical component integrated in the search engine, then in this step, after receiving the search request sent by the user, the device for determining the recommended words will search according to the search request. The included q...
Embodiment 2
[0058] Embodiment 2 of the present application describes the scheme of Embodiment 1 of the present application in detail through specific examples.
[0059] In the solution of the second embodiment, it is necessary to analyze the user's behavior within a set time period, and generate a category feature model of the user behavior and a word feature model of the user behavior. The modeling process of the category feature model and the word feature model will be described in detail below.
[0060] 1. The modeling process of the category feature model:
[0061] The query words and documents browsed by the user in the set time period of history can reflect the user's interest field, and the categories of the query words and the subject terms of the browsed documents can reflect the user's interest in various categories. The degree of interest, the degree of interest of users in various categories can be described through the model based on vector space, as shown in formula (1):
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Embodiment 3
[0155] Embodiment 3 of the present application also provides a device for determining recommended words, such as image 3As shown, it includes: a receiving module 11, a candidate set determining module 12, a correlation determining module 13 and a recommendation module 14, wherein: the receiving module 11 is used to receive a search request containing query words sent by a user; the candidate set determining module 12 is used to According to the pre-stored word sets used by a plurality of users, the word set that contains the query word is used as the candidate word set; the correlation determination module 13 is used to determine the correlation between the candidate word and the query word for a plurality of candidate words in the candidate word set degree, and determine the degree of relevance of each word in the word set used by the user who sends the search request to the candidate word; the recommendation module 14 is used to combine the degree of relevance with the query...
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