Abstract: The present disclosure relates to a method and apparatus for knowledge graph construction, storage medium and electronic device. The method for knowledge graph construction, comprises: identifying an entity concept from a title text of a target web page and at least one entity corresponding to the entity concept from a body text of the target web page; constructing a syntax parse tree of the title text based on syntax parse rules of a language to which the title text belongs, and determining, from the syntax parse tree, a modifier for modifying the entity concept; and generating a knowledge graph based on the entity concept, the modifier, and the at least one entity. Through the solution of the present disclosure, knowledge graphs with high accuracy and high recall rates are constructed without structured processing on target web pages.

Abstract: Embodiments of the present disclosure relate to speech tendency classification.

Abstract: Embodiments of the present disclosure relate to feature crossing for machine learning. According to example embodiments of the present disclosure, a method comprises determining a semantic correlation relationship between a plurality of feature categories, the semantic correlation relationship indicating respective degrees of semantic correlation between respective pairs of feature categories among the plurality of feature categories; obtaining at least two features classified in at least two of the plurality of feature categories for machine learning; and performing feature crossing on the at least two features based on the semantic correlation relationship.

Abstract: Embodiments of the present disclosure relate to attribute and rating co-extraction. According to embodiments of the present disclosure, a method is proposed. The method comprises: determining, by a first sub-network of a model, a first feature representation based on a first token contained in a text, the first feature representation indicating semantic information of the first token in the text; determining, by a second sub-network of the model, first attribute information associated with the first token based on the first feature representation, the first attribute information indicating a first attribute involved in the text; and determining, by a third sub-network of the model, first rating information associated with the first token based on the first feature representation, the first rating information indicating a rating related to the first attribute.

Abstract: Embodiments of the present disclosure relate to semantic parsing for short text. According to embodiments of the present disclosure, a method is proposed. The method comprises: obtaining a set of sentences associated with a short text, each of the set of sentences containing all of words in the short text; determining a set of syntactic features associated with the set of sentences, each of the set of syntactic features indicating at least one of a constituency relation and a dependency relation of the corresponding sentence; and determining a semantic structure of the short text based on the set of syntactic features.

Abstract: Implementations of the present disclosure relate to methods, devices, and computer program products of extracting a feature for multimedia data that comprises a plurality of medium types. In a method, a first feature is determined for a first medium type in the plurality of medium types by masking a portion in a first medium object with the first medium type. A second feature is determined for a second medium type other than the first medium type in the plurality of medium types. The feature is generated for the multimedia data based on the first and second features. With these implementations, multiple medium types are considered in the feature extraction, and thus the feature may fully reflect various aspects of the multimedia data in an accurate way.

Abstract: There are provided methods, devices, and computer program products for similarity determination. In a method, first and second access data are obtained for a first and a second group of users who access a first and a second website, respectively. A first and a second jump path are generated for the first and second groups of users based on the first and second access data, respectively. The first and second jump paths describe access history for the first and second groups of users among webpages in the first and second websites, respectively. A similarity is determined between the first and second websites based on the first and second jump paths. Here, access data are used for similarity determination and unvisited webpages are not considered in the similarity determination. Therefore, the computation workload may be lowered, and the noise caused by the unvisited webpages may be reduced.

Abstract: Embodiments of the present invention pertain to determining the cleanliness of a part used in manufacturing by selectively detecting particles substantially comprised of hard contaminant. According to one embodiment, filtered particles captured on a filter are received at a selective particle detection device. The selective particle detection device determines if at least one of the filtered particles is substantially comprised of hard contaminant. Examples of hard contaminant include silicate, carbide, and ceramic. The determination does not require detecting particles which are not substantially comprised of hard contaminant.

Abstract: Embodiments of the present invention pertain to extracting particles from a slider to enable particle quantification. According to one embodiment, a slider, which is associated with a head stack assembly, is submerged into a solution. Particles are extracted from the slider without extracting particles from the entire head stack assembly.

Abstract: A new and distinct cultivar of Rhododendron plant named ‘Spring Mate’, characterized by its upright to broadly spreading and mounding plant habit; moderately vigorous growth habit and moderate growth rate; freely branching habit and dense and bushy appearance; dark green-colored leaves; freely flowering habit; ruffled semi-double flowers that are vivid reddish orange in color; and good garden performance and temperature tolerance.