Abstract: The present disclosure proposes a method, apparatus and computer-readable medium for sequential recommendation based on cross-domain behavior data. A target user representation of a target user may be generated based on a historical content item sequence of the target user. A cross-domain behavior sequence set may be extracted from a log of a network application. A cross-domain sequence representation set corresponding to the cross-domain behavior sequence set may be generated. A similar sequence representation set similar to the target user representation may be retrieved from the cross-domain sequence representation set. An interaction probability set of the target user interacting with a candidate content item set may be predicted based on the target user representation and the similar sequence representation set.

Abstract: The present technology relates to systems and methods that implement a framework for providing context-aware browser tab recommendations. The present framework allows a web browser to provide a user with recommended web pages in the form of browser tab shortcuts based on the content of the web page the user is currently viewing. When a user clicks on one of the browser tab shortcuts, a new tab is opened in the web browser to display the recommend web page. The browser tab shortcuts may be determined to anticipate the next website the user may want to view or other form of relevance.

Abstract: The present disclosure proposes a method, an apparatus and a computer program product for entity extraction based on edge computing. A web document may be obtained. A text feature of the web document may be identified. A visual feature corresponding to the text feature may be identified. An entity type sequence corresponding to the web document may be extracted based on the text feature and the visual feature.

Abstract: The present disclosure proposes a method and apparatus for multi-model joint denoising training. Multiple models may be obtained. A set of training samples may be denoised through the multiple models. The multiple models may be trained with the set of denoised training samples.

Abstract: The present disclosure proposes a method, apparatus and computer program product for hierarchical representation learning of user interest. A historical content item sequence of a user may be obtained. A topic and a text of each historical content item in the historical content item sequence may be identified, to obtain a topic sequence and a text sequence corresponding to the historical content item sequence. A comprehensive topic representation may be generated based on the topic sequence. A comprehensive text representation may be generated based on the text sequence. A user interest representation of the user may be generated based on the comprehensive topic representation and the comprehensive text representation.

Abstract: The present disclosure proposes a method, apparatus and computer program product for sentence representation generation for cross-lingual retrieval. A target sentence may be obtained. An initial target sentence representation of the target sentence may be generated through an encoder, the encoder pretrained through a contrastive context prediction mechanism. A target sentence representation of the target sentence for cross-lingual retrieval may be generated based on the initial target sentence representation through cross-lingual calibration.

Abstract: The present disclosure proposes a method and apparatus for representation learning of cross-language texts. A source language text and a target language text may be obtained. An initial joint representation of the source language text and the target language text may be generated. Relations among a plurality of words in the source language text and the target language text may be identified. A joint representation of the source language text and the target language text may be generated based on the initial joint representation and the relations. The joint representation may be projected to at least a target language representation corresponding to the target language text.

Abstract: The present disclosure proposes a method and apparatus for multi-model joint denoising training. Multiple models may be obtained. A set of training samples may be denoised through the multiple models. The multiple models may be trained with the set of denoised training samples.

Abstract: A method and apparatus for providing recommended contents. The method comprises: A search query being received; an event being selected from a predetermined event set based on the search query; the recommended contents being provided in a structured template including one or more elements; each element is associated with a feature of the event; each feature of the event corresponds to a search intent. Each element includes one or more sub-contents, and each sub-content is correlated to corresponding recommended contents.

Abstract: In embodiments of the present disclosure, there is provided an assertion-based question answering manner. After a question and the related passage are obtained, an assertion answer to the question is determined based on content of the passage, and the assertion answer has a predetermined structure and represents a complete semantic meaning. Then, the assertion answer to the question may be outputted to the user. In the embodiments of the present disclosure, the question and the relevant passage are used as input, and a semi-structured assertion answer is output. The assertion answer according to embodiments of the present disclosure can provide richer semantic content than the traditional short answer, and provide a more concise expression than the traditional long answer, thereby ensuring accuracy of the answer while improving the user experience.

Abstract: In embodiments of the present disclosure, there is provided an assertion-based question answering manner. After a question and the related passage are obtained, an assertion answer to the question is determined based on content of the passage, and the assertion answer has a predetermined structure and represents a complete semantic meaning. Then, the assertion answer to the question may be outputted to the user. In the embodiments of the present disclosure, the question and the relevant passage are used as input, and a semi-structured assertion answer is output. The assertion answer according to embodiments of the present disclosure can provide richer semantic content than the traditional short answer, and provide a more concise expression than the traditional long answer, thereby ensuring accuracy of the answer while improving the user experience.

Abstract: A method and apparatus for providing recommended contents. The method comprises: A search query being received; an event being selected from a predetermined event set based on the search query; the recommended contents being provided in a structured template including one or more elements; each element is associated with a feature of the event; each feature of the event corresponds to a search intent. Each element includes one or more sub-contents, and each sub-content is correlated to corresponding recommended contents.