239 results about "Context vector" patented technology

A system and method for generating context vectors for use in storage and retrieval of documents and other information items. Context vectors represent conceptual relationships among information items by quantitative means. A neural network operates on a training corpus of records to develop relationship-based context vectors based on word proximity and co-importance using a technique of “windowed co-occurrence”. Relationships among context vectors are deterministic, so that a context vector set has one logical solution, although it may have a plurality of physical solutions. No human knowledge, thesaurus, synonym list, knowledge base, or conceptual hierarchy, is required. Summary vectors of records may be clustered to reduce searching time, by forming a tree of clustered nodes. Once the context vectors are determined, records may be retrieved using a query interface that allows a user to specify content terms, Boolean terms, and / or document feedback. The present invention further facilitates visualization of textual information by translating context vectors into visual and graphical representations. Thus, a user can explore visual representations of meaning, and can apply human visual pattern recognition skills to document searches.

Context-specific transaction proposals are automatically generated and presented to a user who expresses interest in a particular topic. A user viewing a World Wide Web page or other content item activates an interface to indicate that he or she is interested in additional information related to the subject of the page. A context vector or other representation of the content of the page being viewed is transmitted to an information server, which identifies possible transactions related to the content and proposes one or more of these transactions to the user. Transaction proposals can be presented together with a contextual search interface that allows the user to submit zero or more search terms together with the context vector as a search query.

Context-specific transaction proposals are automatically generated and presented to a user who expresses interest in a particular topic. A user viewing a World Wide Web page or other content item activates an interface to indicate that he or she is interested in additional information related to the subject of the page. A context vector or other representation of the content of the page being viewed is transmitted to an information server, which identifies possible transactions related to the content and proposes one or more of these transactions to the user. Transaction proposals can be presented together with a contextual search interface that allows the user to submit zero or more search terms together with the context vector as a search query.

The invention discloses a method for determining target information. The method includes the following steps that encoding is conducted on to-be-processed text information to obtain a source-end vector expression sequence; according to the source-end vector expression sequence, a source-end context vector corresponding to the first moment is obtained, wherein the source-end context vector is used for expressing to-be-processed source-end content; according to the source-end vector expression sequence and the source-end context vector, a first translation vector and / or a second translation vector are / is determined, wherein the first translation vector indicates the source-end content which is not translated in the source-end vector expression sequence within the first moment, and the second translation vector indicates the source-end content which is translated in the source-end vector expression sequence within the second moment; decoding is conducted on the first translation vector and / or a second translation vector and the source-end context vector so as to obtain the target information of the first moment. The invention further provides a method of translation and a device for determining the target information. According to the method for determining the target information, the model training difficulty of a decoder can be reduced, and the translation effect of a translation system is improved.

Systems and methods are provided for implementing searches using contextual information associated with a Web page (or other document) that a user is viewing when a query is entered. The page includes a contextual search interface that has an associated context vector representing content of the page. When the user submits a search query via the contextual search interface, the query and the context vector are both provided to the query processor and used in responding to the query.

The invention discloses a dynamic link prediction method for a space-time attention deep model, and the method comprises the following steps: taking an adjacent matrix A corresponding to a dynamic network as an input, and the dynamic network comprises a social network, a communication network, a scientific cooperation network or a social security network; extracting a hidden layer vector {ht-T,..., ht-1} from the hidden layer vectors {ht-T,..., ht-1} by means of an LSTM-attention model, calculating a context vector at according to the hidden layer vectors {ht-T,..., ht-1} at T moments, and inputting the context vector at the T moments into a decoder as a space-time feature vector; and decoding the input time feature vector at by adopting a decoder, and outputting a probability matrix whichis obtained by decoding and is used for representing whether a link exists between the nodes or not, thereby realizing the prediction of the dynamic link. According to the dynamic link prediction method, link prediction of the end-to-end dynamic network is realized by extracting the spatial and temporal characteristics of the dynamic network.

A method and apparatus for determining contexts of information analyzed. Contexts may be determined for words, expressions, and other combinations of words in bodies of knowledge such as encyclopedias. Analysis of use provides a division of the universe of communication or information into domains, and selects words or expressions unique to those domains of subject matter as an aid in classifying information. A vocabulary list is created with a macro-context (context vector) for each, dependent upon the number of occurrences of unique terms from a domain, over each of the domains. This system may be used to find information or classify information by subsequent inputs of text, in calculation of macro-contexts, with ultimate determination of lists of micro-contests including terms closely aligned with the subject matter.

The present invention relates to a neural machine translation method for introducing source language block information to encode. The method comprises: inputting bilingual sentence-level parallel data, and carrying out word segmentation on the source language and the target language respectively to obtain bilingual parallel sentence pairs after being subject to word segmentation; encoding the source sentence in the bilingual parallel sentence pairs after being subject to word segmentation according to the time sequence, obtaining the state of each time sequence on the hidden layer of the lastlayer, and segmenting the input source sentence by blocks; according to the state of each time sequence of the source sentence and the segmentation information of the source sentence, obtaining the block encoding information of the source sentence; combing the time sequence encoding information with the block encoding information to obtain final source sentence memory information; and by dynamically querying the source sentence memory information, using attention mechanism to generate a context vector at each moment through a decoder network, and extracting feature vectors for word prediction.According to the method provided by the present invention, block segmentation is automatically carried out on the source sentence without the need of any pre-divided sentence to participate in the training, and the method can capture the latest and the best block segmentation manner of the source sentence.