37 results about "Document summarization" patented technology

The disclosure generally relates to document summarization. Given a document, summarization can be defined as picking k sentences from the original document D such that the constructed summary exhibits two key properties: coverage and orthogonality. In one embodiment of the disclosure, the two requirements are captured in a combinatorial formulation of the problem and presented as an algorithms.

A real-time interactive document summarization system which allows the user to continuously control the amount of detail to be included in a document summary.

The present invention discloses a pre-processing summarization technique that makes use of knowledge specific to the electronic mail domain to pre-process an electronic mail message so that commercially-available document summarization software can subsequently generate a more useful summary from the message. The summarization technique removes extraneous headers, quoted text, forward information, and electronic signatures, leaving more useful text to be summarized. If an enclosing electronic mail thread exists, the summarization technique uses the electronic mail message's ancestors to provide additional context for summarizing the electronic mail message. The disclosed system can be used with IBM Lotus Notes and Domino infrastructure, along with existing single-document summarizer software, to generate a summary of the discourse activity in an electronic mail thread dynamically. The summary may be further augmented to list any names, dates, and names of companies that are present in the electronic mail message being summarized.

A system for generating a summary of a plurality of documents and presenting the summary information to a user is provided which includes a computer readable document collection containing a plurality of related documents stored in electronic form. Documents can be pre-processed to group documents into document clusters. The document clusters can also be assigned to predetermined document categories for presentation to a user. A number of multiple document summarization engines are provided which generate summaries for specific classes of multiple documents clusters. A summarizer router is employed to determining a relationship of the documents in a cluster and select one of the document summarization engines for use in generating a summary of the cluster. A single event engine is provided to generate summaries of documents which are closely related temporally and to a specific event. A dissimilarity engine for multiple document summary generation is provided which generates summaries of document clusters having documents with varying degrees of relatedness. A user interface is provided to display categories, cluster titles, summaries, related images.

Topicality scores are determined for a number of phrasal expressions in documents. Phrasal expressions may be noun phrases, with or without corresponding prepositional phrases, subject-verb pairs, and verb-object pairs. The documents describe some topic or multiple topics. Techniques can be used to determined how the phrasal expression compares with the topic or topics being described in the documents. Specificities are determined for the phrasal expressions. Techniques may be used to determine whether phrasal expressions are more or less specific than other phrasal expressions. An order is determined for the phrasal expressions by using the topicality scores and the specificities. The order may be represented as a phrasal expression tree, for example. The phrasal expression tree may be displayed to a user, and the user can navigate through the phrasal expression tree, and therefore through the one or more documents.

System for generating a summary of a plurality of documents is provided. The system includes a computer readable document collection containing a plurality of related documents stored in electronic form therein, a plurality of forms of multiple document summarization engines, and a router for determining a temporal relationship of at least a subset of the documents in the collection and selecting one of the plurality of forms of multiple document summarization engines for generating a summary of the subset of documents based on the temporal relationship.

The present invention discloses a pre-processing summarization technique that makes use of knowledge specific to the electronic mail domain to pre-process an electronic mail message so that commercially-available document summarization software can subsequently generate a more useful summary from the message. The summarization technique removes extraneous headers, quoted text, forward information, and electronic signatures, leaving more useful text to be summarized. If an enclosing electronic mail thread exists, the summarization technique uses the electronic mail message's ancestors to provide additional context for summarizing the electronic mail message. The disclosed system can be used with IBM Lotus Notes and Domino infrastructure, along with existing single-document summarizer software, to generate a summary of the discourse activity in an electronic mail thread dynamically. The summary may be further augmented to list any names, dates, and names of companies that are present in the electronic mail message being summarized.

The present invention discloses a pre-processing summarization technique that makes use of knowledge specific to the electronic mail domain to pre-process an electronic mail message so that commercially-available document summarization software can subsequently generate a more useful summary from the message. The summarization technique removes extraneous headers, quoted text, forward information, and electronic signatures, leaving more useful text to be summarized. If an enclosing electronic mail thread exists, the summarization technique uses the electronic mail message's ancestors to provide additional context for summarizing the electronic mail message. The disclosed system can be used with IBM Lotus Notes and Domino infrastructure, along with existing single-document summarizer software, to generate a summary of the discourse activity in an electronic mail thread dynamically. The summary may be further augmented to list any names, dates, and names of companies that are present in the electronic mail message being summarized.

A set of documents is annotated by metadata specifying persons associated with documents and their social roles in the documents. The annotated documents define a group of representation modes including at least one content type and at least one social role. An electronic processing device computes a relevance score for a person of interest using a set of queries each having a target social role by performing a sequence of operations that includes the following operations: computing similarities between documents and queries with respect to at least one similarity mode of the group of representation modes; enriching queries or documents to identify and aggregate nearest neighbor documents that are most similar with respect to at least one enrichment mode of the group of representation modes; aggregating over documents; aggregating over queries; and aggregating over at least one of (i) enrichment modes, (ii) similarity modes, and (iii) target social roles.

The invention relates to an evolutionary summarization generation method for internet news events. The evolutionary summarization generation method includes the steps: inputting a related news document set; representing documents as topic facture vectors by an LDA (latent Dirichlet allocation) topic model; clustering the documents represented as the topic facture vectors; calculating local scoresof the documents in each topic; calculating global scores of the documents in each topic; calculating final scores of the documents in each topic; extracting document titles with high scores from eachtopic to serve as a summary according to time sequence; outputting the summary. The dimensions of the topic facture vectors are first preset values, and each cluster represents one topic. According to the evolutionary summarization generation method for the internet news events, the extracted summary has dynamic evolvability and is coherent and strong in readability, and experimental results indicate that the system is greatly improved in terms of redundancy, coherence and dynamic evolvability as compared with a traditional multi-document summarization system.

The invention provides a method and a device for generating a document summarization. The method comprises the following steps: obtaining a document, processing the document by utilizing preset characteristics to obtain a summarization candidate sentence, wherein the preset characteristics comprise keywords, numbers and one or a plurality of sentences and subtitles which are far away from a title contained in the document for a preset range; carrying out compression processing to the summarization candidate sentence; and carrying out postprocessing on the summarization candidate sentence subjected to the compression processing to generate the document summarization. The summarization generated by the method and the device, which are disclosed by the embodiment of the invention, for generating a document summarization is concise and accurate, no redundant information exists in the summarization, a generation process is simple and does not need artificial participation, time for generating the document summarization can be greatly shortened, and efficiency on generating the document summarization is improved.

Provided is an automatic document summarization extraction method based on term vectors. The method includes the steps that S1, a deep neural network model is used for training linguistic data to obtain term vector representation of feature terms; S2, a sentence graph model is constructed; S3, the weights of sentences are calculated; S4, a maximum marginal relevance algorithm is used for generating a summarization. According to the method, a linguistic data set is collected and preprocessed to obtain a training feature linguistic data set, the deep neural network model is used for training the constructed training feature linguistic data set to obtain the term vectors of the feature terms, a candidate document set and a candidate sentence set are obtained from the linguistic data set through preset search terms, the semantic similarity between the senesces is obtained according to the term vectors of the feature terms, and then the semantic relation between every two sentences is obtained. The problem that in a traditional calculation method based on term co-occurrence, calculation errors are caused under the condition that semantic meaning is identical but terms are different is avoided, and therefore the accuracy of similarity calculation and the performance of the summarization are improved.

The invention discloses a topic model based document keyword extraction method and system. The document keyword extraction method comprises the following steps of document information preprocessing, document structure graph construction, document topic distribution extraction, word weight extraction and keyword generation. The document keyword extraction system comprises the following modules: a document information preprocessing module, a document structure graph construction module, a document topic distribution extraction module, a word weight extraction module and a keyword generation module. According to the method and system, extracted keywords are more reasonable and related to a topic of a document more closely; and partial deficiencies in the keyword extraction field at present are overcome, a better document summarization effect is achieved, and a user can conveniently and quickly know an abstract of the document.