Abstract: Embodiments of the present disclosure disclose an Internet text mining-based method and apparatus for judging the validity of a point of interest. An implementation of the method includes: determining a search word set for indicating a to-be-detected point of interest; performing a search by using a determined search word as a search keyword, to obtain a description information set for describing the to-be-detected point of interest; and inputting a name of the to-be-detected point of interest and description information in the description information set into a pre-established validity discriminant model, to obtain a status label for indicating validity of the to-be-detected point of interest. This implementation enables timely discovery of invalid POI information. Thus, more accurate information are provided for users, user needs are met, and user experience is improved.

Abstract: The present disclosure provides a method of training a descriptive text generating model, and a method and apparatus for generating a descriptive text, wherein the method of training a descriptive text generating model comprises: obtaining training data, the training data comprising: a notional word, a first descriptive text and a second descriptive text of the notional word, wherein the second descriptive text is a concise expression of the first descriptive text; regarding the notional word and the first descriptive text of the notional word as input of a seq2seq model, regarding the second descriptive text of the notional word as output of the seq2sequ model, and training the seq2seq model to obtain a descriptive text generating model. The descriptive text generating model according to the present disclosure can implement generation of a concise descriptive text with respect to the notional word in a deep understanding manner.

Abstract: The present disclosure provides a method and apparatus for determining search results, a device and a computer storage medium, wherein the method comprises: obtaining a current query, a historical query sequence of the current query and candidate search results of the current query; inputting the current query, the historical query sequence of the current query and candidate search results of the current query into a search result-sorting model, scoring the candidate search results according to the search result-sorting model, and determining search results corresponding to the current query; wherein the scores rendered by the search result-sorting model for the candidate search results are determined according to a similarity degree between an integrated vector representation of the current query and the historical query sequence of the current query and vector representations of the candidate search results.

Abstract: Embodiments of the present disclosure disclose an Internet text mining-based method and apparatus for judging the validity of a point of interest. An implementation of the method includes: determining a search word set for indicating a to-be-detected point of interest; performing a search by using a determined search word as a search keyword, to obtain a description information set for describing the to-be-detected point of interest; and inputting a name of the to-be-detected point of interest and description information in the description information set into a pre-established validity discriminant model, to obtain a status label for indicating validity of the to-be-detected point of interest. This implementation enables timely discovery of invalid POI information. Thus, more accurate information are provided for users, user needs are met, and user experience is improved.

Abstract: The present disclosure provides a method of training a descriptive text generating model, and a method and apparatus for generating a descriptive text, wherein the method of training a descriptive text generating model comprises: obtaining training data, the training data comprising: a notional word, a first descriptive text and a second descriptive text of the notional word, wherein the second descriptive text is a concise expression of the first descriptive text; regarding the notional word and the first descriptive text of the notional word as input of a seq2seq model, regarding the second descriptive text of the notional word as output of the seq2sequ model, and training the seq2seq model to obtain a descriptive text generating model. The descriptive text generating model according to the present disclosure can implement generation of a concise descriptive text with respect to the notional word in a deep understanding manner.

Abstract: The present disclosure provides a method and apparatus for determining search results, a device and a computer storage medium, wherein the method comprises: obtaining a current query, a historical query sequence of the current query and candidate search results of the current query; inputting the current query, the historical query sequence of the current query and candidate search results of the current query into a search result-sorting model, scoring the candidate search results according to the search result-sorting model, and determining search results corresponding to the current query; wherein the scores rendered by the search result-sorting model for the candidate search results are determined according to a similarity degree between an integrated vector representation of the current query and the historical query sequence of the current query and vector representations of the candidate search results.