Beijing Baidu Netcom Science and Technology Co., Ltd.

Xinwei Feng

Xunchao Song

Huanyu Zhou

Miao Yu

Pengcheng Yuan

Songtai Dai

Ying Li

Wenbin Jiang

Meng Tian

Yong Zhu

Xiaobo Liu

Yajuan Lyu

Yilin Zhang

Renkai Yang

Xuping Cao

Xueqian Wu

Shaoshun Kang

Hongjian Shi

The present disclosure discloses a question analysis method, a device, a knowledge base question answering system and an electronic equipment. The method includes: analyzing a question to obtain N linearized sequences, N being an integer greater than 1; converting the N linearized sequences into N network topology maps; separately calculating a semantic matching degree of each of the N network topology maps to the question; and selecting a network topology map having a highest semantic matching degree to the question as a query graph of the question from the N network topology maps. According to the technology of the present disclosure, the query graph of the question can be obtained more accurately, and the accuracy of the question to the query graph is improved, thereby improving the accuracy of question analysis.

Question analysis method, device, knowledge base question answering system and electronic equipment

The present disclosure discloses a method, apparatus, device, and storage medium for training a model, relates to the technical fields of knowledge graph, natural language processing, and deep learning. The method may include: acquiring a first annotation data set, the first annotation data set including sample data and a annotation classification result corresponding to the sample data; training a preset initial classification model based on the first annotation data set to obtain an intermediate model; performing prediction on the sample data in the first annotation data set using the intermediate model to obtain a prediction classification result corresponding to the sample data; generating a second annotation data set based on the sample data, the corresponding annotation classification result, and the corresponding prediction classification result; and training the intermediate model based on the second annotation data set to obtain a classification model.

Method, apparatus, device and storage medium for training model

A method for processing a sematic description of a text entity is proposed. The method includes: acquiring a plurality of target texts containing a main entity, and extracting related entities describing the main entity from each target text; acquiring a sub-relation vector of a pair of the main entity and each related entity in each target text; calculating a similarity distance of the main entity between different target texts based on the sub-relation vector; and determining a semantic similarity of the main entity descripted in different target texts based on the similarity distance.

Method and apparatus for processing sematic description of text entity, and storage medium

A method and apparatus for mining a general tag, a server and a medium are disclosed. The method can comprise: matching a tag seed rule containing a tag placeholder and an attribute of the tag placeholder with historical search information to determine a matching tag; combining the existing tag seed rule and the matching tag to construct a new search sequence set; and performing a generalization process on search sequences included in the new search sequence set to obtain a new tag seed rule, and returning to perform the operation of matching the new tag seed rule with the historical search information to determine a new tag until the tag and the tag seed rule satisfy a convergence condition. A more comprehensive and profound tag can be mined, and the entire flow of mining the tag can not be dependent on a vertical website.

Method and apparatus for mining general tag, server, and medium

Embodiments of the present disclosure provide a method, apparatus, computer device, and storage medium for verifying community question answer data. The method may include: acquiring a community question answer data set, and generating a plurality of question answer pairs based on the community question answer data set, a question answer pair including: a question, and a to-be-verified answer corresponding to the question; generating an authoritative data set based on data stored in at least one confidence source site; and performing an authority verification on the to-be-verified answer, based on a score of a similarity between the to-be-verified answer and authoritative data in the authoritative data set in at least one dimension.

Method, apparatus, computer device and storage medium for verifying community question answer data

A method for obtaining an answer to a question is provided. The method may include: acquiring a question; determining at least a part of articles in a preset article database as candidate articles, and determining first scores of the candidate articles respectively, the first score of any of the candidate articles representing a matching degree between the candidate article and the question; determining at least a part of texts in each of the candidate articles as candidate texts, and determining second scores of the candidate texts respectively, the second score of any of the candidate texts representing a matching degree between the candidate text and the question; and determining at least a part of the candidate texts as the answer based on a score set of each of the candidate texts, the score set of any of the candidate texts including the second score and the first score.

Method, apparatus, electronic device and computer readable medium for obtaining answer to question

Embodiments of the present disclosure provide a query processing method and an apparatus, a server and a storage medium. The method includes: determining a word vector representation of a query sequence and an entity vector representation of the query sequence respectively based on respective words and respective entities included in the query sequence; determining a word vector representation of a paragraph and an entity vector representation of the paragraph respectively based on respective words and respective entities included in the paragraph; and determining a similarity between the query sequence and the paragraph according to the word vector representation of the query sequence, the entity vector representation of the query sequence, the word vector representation of the paragraph, and the entity vector representation of the paragraph.

Query processing method, apparatus, server and storage medium

Embodiments of the disclosure disclose a method and apparatus for generating information. A specific embodiment of the method comprises: acquiring a historical click log, the historical click log comprising a historical search term and a clicked historical search result corresponding to the historical search term; determining whether matching clicked historical search results exist in the historical click log; establishing a synonymous relationship between historical search terms corresponding to the matching clicked historical search results, in response to determining the matching clicked historical search results existing in the historical click log; and generating a relational word list based on the established synonymous relationship. The embodiment helps to enrich the content of the relational word list, and improve the coverage of the relational word list.

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Beijing, China

Xinwei Feng