Abstract: Embodiments of the present disclosure disclose a method and apparatus for constructing a quality evaluation model, an electronic device and a computer-readable storage medium. A specific implementation mode of the method comprises: acquiring samples of knowledge contents; extracting statistical features, semantic features, and image features respectively from the samples of knowledge contents; and constructing a quality evaluation model for knowledge according to the statistical features, the semantic features, and the image features. On the basis of the prior art, this implementation mode additionally uses semantic features and image features of knowledge contents to construct a more accurate quality evaluation model based on multi-dimensional features that characterize the actual quality of a knowledge, which may well discover some brief but very useful summary knowledge in an enterprise and may recommend high-quality knowledge more accurately for employees in the enterprise.

Abstract: A method for denoising click data includes: acquiring a set of click data including pieces of first click data and a real label corresponding to each piece of first click data; extracting feature vectors of each piece of first click data with a graph model; dividing the feature vectors into sets of feature vectors; obtaining trained binary classification models by training binary classification models with the sets of feature vectors; for each of the feature vectors, obtaining prediction values corresponding to the feature vector by predicting the feature vector with the trained binary classification models, and calculating a prediction label of the feature vector based on the prediction values of the feature vector; and removing noise data in the pieces of first click data, based on the pieces of first click data, the real label and the prediction label of each piece of first click data.

Abstract: The present disclosure provides a pre-training method for a sentiment analysis model and an electronic device, which relates to a field of artificial intelligence technologies. The method includes: based on a given seed sentiment dictionary, performing sentimental knowledge detection on a training corpus in a training corpus set, and determining a detection sentiment word and a detection word pair of the training corpus; according to preset mask processing rules, performing mask process on the training corpus to generate a masked corpus; performing encoding and decoding on the masked corpus by using a preset encoder and decoder to determine the detection sentiment word and the detection word pair of the training corpus; and updating the preset encoder and decoder according to a difference between prediction sentiment word and the detection sentiment word, and a difference between prediction word pair and the detection word pair.

Abstract: The present disclosure discloses a comment information processing method and apparatus, and a medium. The specific implementation solution is: in response to a user operation, determining an opinion category corresponding to each opinion phrase in a comment opinion dictionary; obtaining a target corpus matching each opinion phrase from a plurality of comment corpora; for each opinion phrase, using a corresponding opinion category to label the target corpus matching each opinion phrase to obtain a first training sample; and training a classification model with the first training sample to identify the opinion category of a comment by using a trained classification model.

Abstract: A method for generating a tag of a video, an electronic device, and a storage medium are related to a field of natural language processing and deep learning technologies. The detailed implementing solution includes: obtaining multiple candidate tags and video information of the video; determining first correlation information between the video information and each of the multiple candidate tags; sorting the multiple candidate tags based on the first correlation information to obtain a sort result; and generating the tag of the video based on the sort result.

Abstract: The disclosure provides a method for searching an instant messaging object, an electronic device and a storage medium. The method includes: receiving a search request of a first object, and determining a type of the search request; obtaining at least one recall set of the first object based on a client-side search engine in an instant messaging system in response to the type of the search request being a first type; obtaining at least one candidate object corresponding to a search keyword in the search request based on the search keyword and the at least one recall set; obtaining feature information of each candidate object; and responding to the search request by sorting the at least one candidate object based on the feature information.

Abstract: A method for generating an account intimacy includes: obtaining a set of accounts in an instant messaging (IM) group; obtaining a communication frequency between two accounts in the set of accounts within a preset time period; generating a communication network graph based on the communication frequency; obtaining an embedding vector of each account output by a graph model, in which the graph model is trained based on the communication network graph; and generating an intimacy between two accounts based on the embedding vectors of the two accounts.

Abstract: A cross-modality processing method is related to a field of natural language processing technologies. The method includes: obtaining a sample set, wherein the sample set includes a plurality of corpus and a plurality of images; generating a plurality of training samples according to the sample set, in which each of the plurality of the training samples is a combination of at least one of the plurality of the corpus and at least one of the plurality of the images corresponding to the at least one of the plurality of the corpus; adopting the plurality of the training samples to train a semantic model, so that the semantic model learns semantic vectors containing combinations of the corpus and the images.

Abstract: The present disclosure provides a method of recommending a document, an electronic device, and a storage medium, relating to fields of intelligent recommendation, deep learning etc. The method of recommending a document includes: acquiring a document operated by a user, as a reference document; determining, from a plurality of initial documents, at least one candidate document for the reference document, wherein a document content of each candidate document is associated with a document content of the reference document, based on preset knowledge system data; and recommending a target document in the at least one candidate document to the user, the target document including a document that the user is currently interested in and a document that the user is interested in after a preset time period.

Abstract: A document recommendation method based on a semantic tag and a document recommendation device. The method includes: for each document, acquiring a first candidate tag set corresponding to the document, and processing each first candidate tag in the first candidate tag set corresponding to the document to obtain a second candidate tag set corresponding to the document; performing normalization processing on each second candidate tag in the second candidate tag set corresponding to the document to obtain a third candidate tag set corresponding to the document; performing expanding process on each third candidate tag in the third candidate tag set corresponding to the document, and acquiring a fourth candidate tag set corresponding to the document, to form a document library having semantic tags; and recommending a target document obtained from the document library having semantic tags to the user, according to historical semantic tag.

Abstract: A method for generating a tag of a video, an electronic device, and a storage medium are related to a field of natural language processing and deep learning technologies. The detailed implementing solution includes: obtaining multiple candidate tags and video information of the video; determining first correlation information between the video information and each of the multiple candidate tags; sorting the multiple candidate tags based on the first correlation information to obtain a sort result; and generating the tag of the video based on the sort result.

Abstract: The present disclosure provides an information processing method, an electronic device and a computer storage medium, and relates to a field of information processing. The method includes: obtaining a first content based on a first search keyword indicating a first event and a second search keyword indicating an object related to the first event; obtaining information associated with an attribute of the object from the first content; obtaining a second content based on the first search keyword and a third search keyword indicating a result at least caused by the first event; and generating statistical data associated with the first event based on the information and the second content.

Abstract: A cross-modality processing method is related to a field of natural language processing technologies. The method includes: obtaining a sample set, wherein the sample set includes a plurality of corpus and a plurality of images; generating a plurality of training samples according to the sample set, in which each of the plurality of the training samples is a combination of at least one of the plurality of the corpus and at least one of the plurality of the images corresponding to the at least one of the plurality of the corpus; adopting the plurality of the training samples to train a semantic model, so that the semantic model learns semantic vectors containing combinations of the corpus and the images.

Abstract: Embodiments of the present disclosure disclose a method and apparatus for constructing a quality evaluation model, an electronic device and a computer-readable storage medium. A specific implementation mode of the method comprises: acquiring samples of knowledge contents; extracting statistical features, semantic features, and image features respectively from the samples of knowledge contents; and constructing a quality evaluation model for knowledge according to the statistical features, the semantic features, and the image features. On the basis of the prior art, this implementation mode additionally uses semantic features and image features of knowledge contents to construct a more accurate quality evaluation model based on multi-dimensional features that characterize the actual quality of a knowledge, which may well discover some brief but very useful summary knowledge in an enterprise and may recommend high-quality knowledge more accurately for employees in the enterprise.

Abstract: The present disclosure discloses a comment information processing method and apparatus, and a medium. The specific implementation solution is: in response to a user operation, determining an opinion category corresponding to each opinion phrase in a comment opinion dictionary; obtaining a target corpus matching each opinion phrase from a plurality of comment corpora; for each opinion phrase, using a corresponding opinion category to label the target corpus matching each opinion phrase to obtain a first training sample; and training a classification model with the first training sample to identify the opinion category of a comment by using a trained classification model.

Abstract: The present disclosure provides a pre-training method for a sentiment analysis model and an electronic device, which relates to a field of artificial intelligence technologies. The method includes: based on a given seed sentiment dictionary, performing sentimental knowledge detection on a training corpus in a training corpus set, and determining a detection sentiment word and a detection word pair of the training corpus; according to preset mask processing rules, performing mask process on the training corpus to generate a masked corpus; performing encoding and decoding on the masked corpus by using a preset encoder and decoder to determine the detection sentiment word and the detection word pair of the training corpus; and updating the preset encoder and decoder according to a difference between prediction sentiment word and the detection sentiment word, and a difference between prediction word pair and the detection word pair.

Abstract: The present disclosure provides a method and a device for generating a text tag. The method includes: performing keyword extraction using strategies corresponding to respective tag types on a target text, to obtain one or more candidate tags of the respective tag types for the target text, wherein the tag type includes at least one of an entity word, a segment text and a topic; performing reduplication removing between different tag types on the one or more candidate tags of the respective tag types to obtain one or more validated candidate tags; and determining one or more target tags of the target text based on the one or more validated candidate tags.

Abstract: The present disclosure provides a document recommendation method based on a semantic tag and a document recommendation device. The method includes: for each document, acquiring a first candidate tag set corresponding to the document, and processing each first candidate tag in the first candidate tag set corresponding to the document to obtain a second candidate tag set corresponding to the document; performing normalization processing on each second candidate tag in the second candidate tag set corresponding to the document to obtain a third candidate tag set corresponding to the document; performing expanding process on each third candidate tag in the third candidate tag set corresponding to the document, and acquiring a fourth candidate tag set corresponding to the document, to form a document library having semantic tags; and recommending a target document obtained from the document library having semantic tags to the user, according to historical semantic tag.

Abstract: The present disclosure provides a searching method and apparatus, a device and a non-volatile computer memory medium. According to embodiments of the present disclosure, it is possible to output the clustered search result under the potential demand by obtaining a search result according to the obtained query keyword, and then clustering the search result under the potential demand of the query keyword. Since the user might have demands in one or more aspects, clustering the search result corresponding to the query keyword under one or more potential demands of the query keyword can enable the user to easily obtain content in a class under a certain potential demand, and can effectively satisfy the user's relevant demands appearing during the search.

Abstract: The present disclosure provides a method and a device for generating a text tag. The method includes: performing keyword extraction using strategies corresponding to respective tag types on a target text, to obtain one or more candidate tags of the respective tag types for the target text, wherein the tag type includes at least one of an entity word, a segment text and a topic; performing reduplication removing between different tag types on the one or more candidate tags of the respective tag types to obtain one or more validated candidate tags; and determining one or more target tags of the target text based on the one or more validated candidate tags.