1. Articles in category: Summarization

    25-48 of 1859 « 1 2 3 4 5 ... 76 77 78 »
    1. Method and system for video summarization

      A video summary method comprises dividing a video into a plurality of video shots, analyzing each frame in a video shot from the plurality of video shots, determining a saliency of each frame of the video shot, determining a key frame of the video shot based on the saliency of each frame of the video shot, extracting visual features from the key frame and performing shot clustering of the plurality of video shots to determine concept patterns based on the visual features. The method further comprises fusing different concept patterns using a saliency tuning method and generating a summary of ...

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    2. Real-Time Web Scale Event Summarization Using Sequential Decision Making. (arXiv:1605.03664v1 [cs.CL])

      We present a system based on sequential decision making for the online summarization of massive document streams, such as those found on the web. Given an event of interest (e.g. "Boston marathon bombing"), our system is able to filter the stream for relevance and produce a series of short text updates describing the event as it unfolds over time.

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      Mentions: Boston
    3. Corpus-Based Problem Selection for EHR Note Summarization.

      Corpus-Based Problem Selection for EHR Note Summarization.

      AMIA Annu Symp Proc. 2010;2010:817-21

      Authors: Van Vleck TT, Elhadad N

      Abstract Physicians have access to patient notes in volumes far greater than what is practical to read within the context of a standard clinical scenario. As a preliminary step toward being able to provide a longitudinal summary of patient history, methods are examined for the automated extraction of relevant patient problems from existing clinical notes.

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    4. Systems and methods for generating summaries of documents

      Systems and methods for summarizing online articles for consumption on a user device are disclosed herein. The system extracts the main body of an article's text from the HTML code of an online article. The system may then classify the extracted article into one of several different categories and removes duplicate articles. The system breaks down the article into its component sentences, and each sentence is classified into one of three categories: (1) potential candidate sentences that may be included in the generated summary; (2) weakly rejected sentences that will not be included in the summary but may be ...

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    5. Fast title/summary extraction from long descriptions

      Techniques are described herein for automatic generation of a title or summary from a long body of text. A grammatical tree representing one or more sentences of the long body of text is generated. One or more nodes from the grammatical tree are selected to be removed. According to one embodiment, a particular node is selected to be removed based on its position in the grammatical tree and its node-type, where the node type represents a grammatical element of the sentence. Once the particular node is selected, a branch of the tree is cut at the node. After branch has ...

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    6. Medical analysis application and response system

      Disclosed is an apparatus and method of communicating with a user of a wireless device and processing message delivery. One example method of operation may include identifying a group of participants to receive a broadcast message transmitted from a wireless device, transmitting at least one broadcast message from the wireless device to a plurality of computing devices corresponding to the group of participants, receiving a plurality of response messages responsive to the at least one transmitted broadcast message, examining the plurality of response messages and extracting content of the plurality of response messages, generating a summary message based on the ...

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    7. AttSum: Joint Learning of Focusing and Summarization with Neural Attention. (arXiv:1604.00125v1 [cs.IR])

      Query relevance ranking and sentence saliency ranking are the two main tasks in extractive query-focused summarization. Previous supervised summarization systems often perform the two tasks in isolation. However, since reference summaries are the trade-off between relevance and saliency, using them as supervision, neither of the two rankers could be trained well. This paper proposes a novel summarization system called AttSum, which tackles the two tasks jointly.

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    8. Learning-Based Single-Document Summarization with Compression and Anaphoricity Constraints. (arXiv:1603.08887v1 [cs.CL])

      We present a discriminative model for single-document summarization that integrally combines compression and anaphoricity constraints. Our model selects textual units to include in the summary based on a rich set of sparse features whose weights are learned on a large corpus. We allow for the deletion of content within a sentence when that deletion is licensed by compression rules; in our framework, these are implemented as dependencies between subsentential units of text.

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    9. Neural Summarization by Extracting Sentences and Words. (arXiv:1603.07252v1 [cs.CL])

      Traditional approaches to extractive summarization rely heavily on human-engineered features. In this work we propose a data-driven approach based on neural networks and continuous sentence features. We develop a general framework for single-document summarization composed of a hierarchical document encoder and an attention-based extractor. This architecture allows us to develop different classes of summarization models which can extract sentences or words.

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    10. Clinical application of the integrated multicenter discharge summary database.

      Clinical application of the integrated multicenter discharge summary database.

      Clinical application of the integrated multicenter discharge summary database.

      Stud Health Technol Inform. 2015;216:1120

      Authors: Takahiro S, Shunsuke D, Yutaka H, Masayuki H, Yasushi M, Gen S, Mitsuhiro T, Shusaku T, Hideto Y, Katsuhiko T

      Abstract We performed the multi-year project to collect discharge summary from multiple hospitals and made the big text database to build a common document vector space, and developed various applications.

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    11. De-duplication deployment planning

      Assignment of files to a de-duplication domain. Address space of data files is divided into multiple containers. For each of the containers, a file metadata scan is performed to obtain file system metadata, which is aggregated and summarized in a content feature summary. A content feature summary prediction measurement is measured between containers from the generated content feature summary, and files from each container are assigned to a de-duplication domain based upon the content similarity predication measurement.

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    12. Entity category extraction for an entity that is the subject of pre-labeled data

      Summaries of entities (e.g., people, places, things, concepts, etc.) may provide additional useful information to user. For example, a search engine may provide a summary of an entity within search results. A category (e.g., "writer", "politician", etc.) of the entity that is short and concise may be advantageous to provide within a summary of the entity. The category may allow a user to quickly determine whether the information of the entity relates to the intended entity (e.g., search results of an entity as "a writer" vs. search results of an entity as "a politician"). Potential categories and ...

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    13. Paraphrase Generation from Latent-Variable PCFGs for Semantic Parsing. (arXiv:1601.06068v1 [cs.CL])

      One of the limitations of semantic parsing approaches to open-domain question answering is the lexicosyntactic gap between natural language questions and knowledge base entries -- there are many ways to ask a question, all with the same answer. In this paper we propose to bridge this gap by generating paraphrases of the input question with the goal that at least one of them will be correctly mapped to a knowledge-base query.

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    14. Improved Spoken Document Summarization with Coverage Modeling Techniques. (arXiv:1601.05194v1 [cs.CL])

      Extractive summarization aims at selecting a set of indicative sentences from a source document as a summary that can express the major theme of the document. A general consensus on extractive summarization is that both relevance and coverage are critical issues to address. The existing methods designed to model coverage can be characterized by either reducing redundancy or increasing diversity in the summary.

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    15. System, method and computer program product for searching summaries of mobile apps reviews

      A system, method, and computer program product (e.g. mobile App) and/or web-based service is provided to enable users to research online reviews in order to assess the performance and functionality of mobile applications. The system extracts reviews from multiple online sources, including: mobile Apps "stores", blogs, online magazines, websites, etc.; and, utilizes sentiment analysis algorithms and supervised machine learning analysis to present more informative summaries for each App's reviews. Summaries may include: a sentence that encapsulates a sentiment held by many users; the most positive and negative comments; and a list of features with average scores (e ...

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    16. Method and apparatus for summarizing communications

      A method, apparatus and computer program are provided for summarizing one or more communications. The method, apparatus and computer program process and/or facilitate a processing of one or more communications to generate at least one summary. The method, apparatus and computer program further cause, at least in part, a transformation of the at least one summary based, at least in part, on at least one narrative viewpoint. The method, apparatus and computer program further cause, at least in part, a presentation of the transformation.

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    17. Generating News Headlines with Recurrent Neural Networks. (arXiv:1512.01712v1 [cs.CL])

      We describe an application of an encoder-decoder recurrent neural network with LSTM units and attention to generating headlines from the text of news articles. We find that the model is quite effective at concisely paraphrasing news articles. Furthermore, we study how the neural network decides which input words to pay attention to, and specifically we identify the function of the different neurons in a simplified attention mechanism.

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    18. Service monitoring interface

      One or more processing devices cause display of a service-monitoring page having a services summary region and a services aspects region. The services summary region contains an ordered plurality of interactive summary tiles, each summary tile corresponding to a respective service and providing a character or graphical representation of at least one value for an aggregate key performance indicator (KPI) characterizing the respective service as a whole. The services aspects region contains an ordered plurality of interactive aspect tiles, each aspect tile corresponding to a respective aspect KPI and providing a character or graphical representation of one or more values ...

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      Mentions: KPI
    19. Inferring Interpersonal Relations in Narrative Summaries. (arXiv:1512.00112v1 [cs.CL])

      Characterizing relationships between people is fundamental for the understanding of narratives. In this work, we address the problem of inferring the polarity of relationships between people in narrative summaries. We formulate the problem as a joint structured prediction for each narrative, and present a model that combines evidence from linguistic and semantic features, as well as features based on the structure of the social community in the text.

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    20. TGSum: Build Tweet Guided Multi-Document Summarization Dataset. (arXiv:1511.08417v1 [cs.IR])

      The development of summarization research has been significantly hampered by the costly acquisition of reference summaries. This paper proposes an effective way to automatically collect large scales of news-related multi-document summaries with reference to social media's reactions. We utilize two types of social labels in tweets, i.e., hashtags and hyper-links. Hashtags are used to cluster documents into different topic sets.

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    21. Towards Universal Paraphrastic Sentence Embeddings. (arXiv:1511.08198v1 [cs.CL])

      In this paper, we show how to create paraphrastic sentence embeddings using the Paraphrase Database (Ganitkevitch et al., 2013), an extensive semantic resource with millions of phrase pairs. We consider several compositional architectures and evaluate them on 24 textual similarity datasets encompassing domains such as news, tweets, web forums, news headlines, machine translation output, glosses, and image and video captions.

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    22. Bilingual term alignment from comparable corpora in English discharge summary and Chinese discharge summary.

      Bilingual term alignment from comparable corpora in English discharge summary and Chinese discharge summary.

      Bilingual term alignment from comparable corpora in English discharge summary and Chinese discharge summary.

      BMC Bioinformatics. 2015;16:149

      Authors: Xu Y, Chen L, Wei J, Ananiadou S, Fan Y, Qian Y, Chang EI, Tsujii J

      Abstract BACKGROUND: Electronic medical record (EMR) systems have become widely used throughout the world to improve the quality of healthcare and the efficiency of hospital services.

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    25-48 of 1859 « 1 2 3 4 5 ... 76 77 78 »
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