Abstract: According to implementations of the subject matter described herein, a solution is proposed for auto-suggesting. In this solution, a trigger indication for suggesting is provided based on an input sentence. In response to the trigger indication being confirmed, a suggestion for the sentence is provided and the suggestion comprises one or more rich objects. In response to a selection of the suggestion, supplementary information for supplementing the sentence is provided based on at least one selected rich object. In this way, various auto-suggestions comprising rich objects may be provided, and thus rich supplementary information may be provided to supplement the input sentence to enhance the user experience.

Abstract: In embodiments of the present disclosure, there is provided a method for generating a stylized icon automatically. After a query text inputted by a user is obtained, a trained generator is used to generate a structured icon that can characterize a structure of an object, and then the structured icon is stylized, such as performing color padding or adding other styles, so as to generate a high-quality stylized icon for the user. In embodiments of the present disclosure, a structured icon and a stylized icon are generated respectively at two stages, where the structured icon can clearly characterize the structure of the object, while the stylized icon can be richer in color and style. Therefore, the stylized icon generated according to embodiments of the present disclosure has a higher quality and is more realistic, thereby improving the user experience of icon generation.

Abstract: In embodiments of the present disclosure, there is provided a method for generating a stylized icon automatically. After a query text inputted by a user is obtained, a trained generator is used to generate a structured icon that can characterize a structure of an object, and then the structured icon is stylized, such as performing color padding or adding other styles, so as to generate a high-quality stylized icon for the user. In embodiments of the present disclosure, a structured icon and a stylized icon are generated respectively at two stages, where the structured icon can clearly characterize the structure of the object, while the stylized icon can be richer in color and style. Therefore, the stylized icon generated according to embodiments of the present disclosure has a higher quality and is more realistic, thereby improving the user experience of icon generation.

Abstract: The present disclosure provides method and apparatus for document auto-completion. In an aspect, an instruction for creating a document may be received. The document may be presented in response to the instruction, at least a first section in the document including content suggested according to context information associated with the document. An edit operation to the document may be received. Content suggested in response to the edit operation may be presented in at least a second section in the document. In another aspect, context information associated with completion of a document may be identified. Content of at least one section in the document may be generated, the content being suggested based at least on the context information. The content may be presented in the at least one section in the document.

Abstract: A method and apparatus may be used for document auto-completion. In an aspect, an instruction for creating a document may be received. The document may be presented in response to the instruction, at least a first section in the document including content suggested according to context information associated with the document. An edit operation to the document may be received. Content suggested in response to the edit operation may be presented in at least a second section in the document. In another aspect, context information associated with completion of a document may be identified. Content of at least one section in the document may be generated, the content being suggested based at least on the context information. The content may be presented in the at least one section in the document.

Abstract: In accordance with the implementations of the subject matter described herein, there is provided a solution for reusing infographics. In this solution, a group of visual element units is determined from a visual element set comprised in the original infographic. A visual element unit in the group represents an information item in the original infographic. A first correlation between a visual element contained in the visual element unit and the information item and a second correlation between the visual element unit and a further visual element unit in the group are determined. A description for the original infographic is generated based on the first and second correlations. A target infographic is generated by updating the group of visual element units at least based on the description and the target information. In this way, infographics can be converted into reusable templates, thereby simplifying reuse of such infographics and improving user experience.

Abstract: Various implementations of the present disclosure relate to style transfer. In some implementations, a computer-implemented method comprises: obtaining a target object having a first style, a style of the target object being editable; obtaining a reference image including a reference object; obtaining a second style of the reference object, the second style of the reference object being extracted from the reference image; and applying the second style to the target object.

Abstract: Various implementations of the present disclosure relate to style transfer. In some implementations, a computer-implemented method comprises: obtaining a target object having a first style, a style of the target object being editable; obtaining a reference image including a reference object; obtaining a second style of the reference object, the second style of the reference object being extracted from the reference image; and applying the second style to the target object.

Abstract: In embodiments of the present disclosure, there is provided a method for generating a stylized icon automatically. After a query text inputted by a user is obtained, a trained generator is used to generate a structured icon that can characterize a structure of an object, and then the structured icon is stylized, such as performing color padding or adding other styles, so as to generate a high-quality stylized icon for the user. In embodiments of the present disclosure, a structured icon and a stylized icon are generated respectively at two stages, where the structured icon can clearly characterize the structure of the object, while the stylized icon can be richer in color and style. Therefore, the stylized icon generated according to embodiments of the present disclosure has a higher quality and is more realistic, thereby improving the user experience of icon generation.

Abstract: The present disclosure provides method and apparatus for document auto-completion. In an aspect, an instruction for creating a document may be received. The document may be presented in response to the instruction, at least a first section in the document including content suggested according to context information associated with the document. An edit operation to the document may be received. Content suggested in response to the edit operation may be presented in at least a second section in the document. In another aspect, context information associated with completion of a document may be identified. Content of at least one section in the document may be generated, the content being suggested based at least on the context information. The content may be presented in the at least one section in the document.

Abstract: Various implementations of the present disclosure relate to style transfer. In some implementations, a computer-implemented method comprises: obtaining a target object having a first style, a style of the target object being editable; obtaining a reference image including a reference object; obtaining a second style of the reference object, the second style of the reference object being extracted from the reference image; and applying the second style to the target object.

Abstract: Systems and methods are disclosed for inferring topics from a file containing both audio and video, for example a multimodal or multimedia file, in order to facilitate video indexing. A set of entities is extracted from the file and linked to produce a graph, and reference information is also obtained for the set of entities. Entities may be drawn, for example, from Wikipedia categories, or other large ontological data sources. Analysis of the graph, using unsupervised learning, permits determining clusters in the graph. Extracting features from the clusters, possibly using supervised learning, provides for selection of topic identifiers. The topic identifiers are then used for indexing the file.

Abstract: Systems and methods are disclosed for inferring topics from a file containing both audio and video, for example a multimodal or multimedia file, in order to facilitate video indexing. A set of entities is extracted from the file and linked to produce a graph, and reference information is also obtained for the set of entities. Entities may be drawn, for example, from Wikipedia categories, or other large ontological data sources. Analysis of the graph, using unsupervised learning, permits determining clusters in the graph. Extracting features from the clusters, possibly using supervised learning, provides for selection of topic identifiers. The topic identifiers are then used for indexing the file.

Abstract: Systems, methods, and computer-readable media for dynamically generating text associated with an advertisement are provided. Core text associated with an advertisement is received from an advertiser, as is at least one attribute relevant to the advertiser and/or a user. Based upon the received attribute(s), it is determined whether customization of the core text is desired. If customization is desired, the core text is modified and presented in association with the advertisement. If customization is not desired, the core text is presented in association with the advertisement. In one embodiment, target advertisement placement information may also be utilized to determine whether customization of the core text is desired.

Abstract: Described herein are techniques for extracting data records containing user-generated content from documents. The documents may be processed into document trees in which sub-trees represent the data records of the document. Domain constraints may be used to locate structured portions of the document tree. For example, anchor trees may be located as being sets of sibling sub-trees with similar tag paths that contain the domain constraints. The anchor trees may then be used to determine a record boundary (e.g., the start offset and length) of the data records. Finally, the data records may be extracted based on the anchor trees and the record boundaries.

Abstract: This disclosure describes, in part, techniques for operating a search query user interface to allow seamless creating, editing and/or refining of a search query using various interactive functions. The techniques described herein may display a search query divided into segments. A selection of a segment of the search query may then be received. One or more alternatives to the selected segment may then be presented. Next, a selection of one of the presented alternative may be received. As a result, the search query may be altered using the selected alternative. Furthermore, the techniques described herein allow a user to operate on a search query using query substitution, expansion, association and/or history functions.

Abstract: Embodiments for a Mining Data Records based on Anchor Trees (MiBAT) process are disclosed. In accordance with at least one embodiment, the MiBAT process extracts data records containing user-generated content from web documents. The web document is processed into a Document Object Model (DOM) tree in which sub-trees of the DOM tree represent the data records of the web document. Domain constraints are used to locate structured portions of the DOM tree. Anchor trees are then located as being sets of sibling sub-trees which contain the domain constraints. The anchor trees are then used to determine a record boundary (i.e. the start offset and length) of the data records. Finally, the data records are extracted based on the anchor trees and the record boundaries.

Abstract: Some implementations disclosed herein provide techniques and arrangements to train a blocking scheme using both labeled data and unlabeled data. For example, training the blocking scheme may include iteratively: learning a conjunction, identifying first matches in the labeled data and the unlabeled data that are uncovered by the conjunction, and identifying second matches in the labeled data and the unlabeled data that are covered by the conjunction. The conjunction learned in each iteration may be combined using a disjunction. A search engine may use the search engine when searching for records that match an entity.

Abstract: This disclosure describes, in part, techniques for operating a search query user interface to allow seamless creating, editing and/or refining of a search query using various interactive functions. The techniques described herein may display a search query divided into segments. A selection of a segment of the search query may then be received. One or more alternatives to the selected segment may then be presented. Next, a selection of one of the presented alternative may be received. As a result, the search query may be altered using the selected alternative. Furthermore, the techniques described herein allow a user to operate on a search query using query substitution, expansion, association and/or history functions.

Abstract: The subject disclosure is directed towards ranking participants in an online platform according to expertise. A competition-based metric is applied to question and answer threads in order to model each thread as a set of comparisons between various groups of the participants. After aggregating comparison results for the question and answer treads, one or more relative expertise scores may be estimated for each participant. Each relative expertise score may correspond to a specific category of questions.