Abstract: This application discloses a summary generation using natural language processing via method, apparatus, and a computer device. The summary generation is implemented by obtaining a document, the document including at least one sentence. The summary generation is further implemented by extracting m candidate sentences from the document by using an extractive model. The summary generation is further implemented by outputting target words according to the m candidate sentences by using an abstractive model, and generating a summary according to the target words.

Abstract: Disclosed are interest tag determining method and device for accurately promoting information for users in a group based on interest tags of the group. This includes obtaining a group identifier and a corresponding group name, obtaining user identifiers corresponding to the group identifier and first user contents of the user identifiers, concatenating the first user contents of the user identifiers corresponding to the group identifier to obtain a first group content of the group identifier, calculating probabilities that the first group content is under the topic identifiers, and determining interest tags of the group identifier according to the probabilities that the first group content is under the topic identifiers and an association relationship between the topic identifiers and the interest tags that is determined through pre-training.

Abstract: An information processing method includes obtaining text information and a sentence set; encoding a sentence in the sentence set using a first encoder to obtain a first encoded vector, and encoding the sentence using a second encoder to obtain a second encoded vector. The first encoded vector is determined according to the sentence, and the second encoded vector is determined according to a feature of the sentence. The method also includes determining a sentence encoded vector according to the first and second encoded vectors; encoding the sentence encoded vector using a third encoder to obtain global information; decoding the global information using a decoder; and determining a probability value corresponding to the sentence. Accordingly, when a deep learning method is used, a manually extracted sentence is further added to perform feature training, to effectively improve a learning capability of a model, thereby improving an information processing capability and effect.

Abstract: This application discloses a summary generation using natural language processing via method, apparatus, and a computer device. The summary generation is implemented by obtaining a document, the document including at least one sentence. The summary generation is further implemented by extracting m candidate sentences from the document by using an extractive model. The summary generation is further implemented by outputting target words according to the m candidate sentences by using an abstractive model, and generating a summary according to the target words.

Abstract: An information processing method includes obtaining text information and a sentence set; encoding a sentence in the sentence set using a first encoder to obtain a first encoded vector, and encoding the sentence using a second encoder to obtain a second encoded vector. The first encoded vector is determined according to the sentence, and the second encoded vector is determined according to a feature of the sentence. The method also includes determining a sentence encoded vector according to the first and second encoded vectors; encoding the sentence encoded vector using a third encoder to obtain global information; decoding the global information using a decoder; and determining a probability value corresponding to the sentence. Accordingly, when a deep learning method is used, a manually extracted sentence is further added to perform feature training, to effectively improve a learning capability of a model, thereby improving an information processing capability and effect.

Abstract: Disclosed are interest tag determining method and device for accurately promoting information for users in a group based on interest tags of the group. This includes obtaining a group identifier and a corresponding group name, obtaining user identifiers corresponding to the group identifier and first user contents of the user identifiers, concatenating the first user contents of the user identifiers corresponding to the group identifier to obtain a first group content of the group identifier, calculating probabilities that the first group content is under the topic identifiers, and determining interest tags of the group identifier according to the probabilities that the first group content is under the topic identifiers and an association relationship between the topic identifiers and the interest tags that is determined through pre-training.

Abstract: A fixing mechanism for a button includes a shelf (11) and a bracket (80). The bracket includes a body (81). A pair of spaced apart first resilient arms (85) extends from an edge of the body 81, and a second resilient arm (83) extends from the edge between the first resilient arms. A free end of each first resilient arm is attached to the shelf, and the second resilient arm is for holding the button.

Abstract: An exemplary mounting apparatus for aiding in mounting a plurality of long expansion cards in electrical devices includes a locating member, and a retention member rotatably attached to the locating member. The locating member includes a base wall, a pair of sidewalls, and a top wall. Pairs of guiding rails extend from the base wall for slidably receiving ends of the expansion cards opposite to ends with cover plates. Two pairs of first positioning blocks extend from the top wall. The retention member includes a base plate, a pair of flanges, and a pair of resilient arms. A plurality of retaining tabs extends from the base plate to abut against top edges of the expansion cards. The flanges are rotatably attached to the sidewalls of the locating member. The resilient arms each include a pair of second positioning blocks for engaging with the first positioning blocks of the locating member.

Abstract: An exemplary mounting apparatus for aiding in mounting a plurality of long expansion cards in electrical devices includes a locating member, and a retention member rotatably attached to the locating member. The locating member includes a base wall, a pair of sidewalls, and a top wall. Pairs of guiding rails extend from the base wall for slidably receiving ends of the expansion cards opposite to ends with cover plates. Two pairs of first positioning blocks extend from the top wall. The retention member includes a base plate, a pair of flanges, and a pair of resilient arms. A plurality of retaining tabs extends from the base plate to abut against top edges of the expansion cards. The flanges are rotatably attached to the sidewalls of the locating member. The resilient arms each include a pair of second positioning blocks for engaging with the first positioning blocks of the locating member.

Abstract: A fixing mechanism for a button includes a shelf (11) and a bracket (80). The bracket includes a body (81). A pair of spaced apart first resilient arms (85) extends from an edge of the body 81, and a second resilient arm (83) extends from the edge between the first resilient arms. A free end of each first resilient arm is attached to the shelf, and the second resilient arm is for holding the button.