1. Articles in category: Semantic

    73-96 of 4027 « 1 2 3 4 5 6 7 ... 166 167 168 »
    1. Attributes as Semantic Units between Natural Language and Visual Recognition. (arXiv:1604.03249v1 [cs.CV])

      Impressive progress has been made in the fields of computer vision and natural language processing. However, it remains a challenge to find the best point of interaction for these very different modalities. In this chapter we discuss how attributes allow us to exchange information between the two modalities and in this way lead to an interaction on a semantic level.

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    2. Capturing Semantic Similarity for Entity Linking with Convolutional Neural Networks. (arXiv:1604.00734v1 [cs.CL])

      A key challenge in entity linking is making effective use of contextual information to disambiguate mentions that might refer to different entities in different contexts. We present a model that uses convolutional neural networks to capture semantic correspondence between a mention's context and a proposed target entity.

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    3. Nonparametric Spherical Topic Modeling with Word Embeddings. (arXiv:1604.00126v1 [cs.CL])

      Traditional topic models do not account for semantic regularities in language. Recent distributional representations of words exhibit semantic consistency over directional metrics such as cosine similarity. However, neither categorical nor Gaussian observational distributions used in existing topic models are appropriate to leverage such correlations. In this paper, we propose to use the von Mises-Fisher distribution to model the density of words over a unit sphere.

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    4. Methods, systems, and computer-readable media for semantically enriching content and for semantic navigation

      Methods, systems and computer-readable media enable various techniques related to semantic navigation. One aspect is a technique for displaying semantically derived facets in the search engine interface. Each of the facets comprises faceted search results. Each of the faceted search results is displayed in association with user interface elements for including or excluding the faceted search result as additional search terms to subsequently refine the search query. Another aspect automatically infers new metadata from the content and from existing metadata and then automatically annotates the content with the new metadata to improve recall and navigation. Another aspect identifies semantic annotations ...

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    5. Semantic Properties of Customer Sentiment in Tweets. (arXiv:1603.07624v1 [cs.CL])

      An increasing number of people are using online social networking services (SNSs), and a significant amount of information related to experiences in consumption is shared in this new media form. Text mining is an emerging technique for mining useful information from the web. We aim at discovering in particular tweets semantic patterns in consumers' discussions on social media.

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    6. Semantic Regularities in Document Representations. (arXiv:1603.07603v1 [cs.CL])

      Recent work exhibited that distributed word representations are good at capturing linguistic regularities in language. This allows vector-oriented reasoning based on simple linear algebra between words. Since many different methods have been proposed for learning document representations, it is natural to ask whether there is also linear structure in these learned representations to allow similar reasoning at document level.

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    7. Learning Executable Semantic Parsers for Natural Language Understanding. (arXiv:1603.06677v1 [cs.CL])

      For building question answering systems and natural language interfaces, semantic parsing has emerged as an important and powerful paradigm. Semantic parsers map natural language into logical forms, the classic representation for many important linguistic phenomena. The modern twist is that we are interested in learning semantic parsers from data, which introduces a new layer of statistical and computational issues.

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    8. A Pilot Study on Modeling of Diagnostic Criteria Using OWL and SWRL.

      A Pilot Study on Modeling of Diagnostic Criteria Using OWL and SWRL.

      A Pilot Study on Modeling of Diagnostic Criteria Using OWL and SWRL.

      Stud Health Technol Inform. 2015;216:1093

      Authors: Hong N, Jiang G, Pathak J, Chute CG

      Abstract The objective of this study is to describe our efforts in a pilot study on modeling diagnostic criteria using a Semantic Web-based approach. We reused the basic framework of the ICD-11 content model and refined it into an operational model in the Web Ontology Language (OWL).

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    9. Constructing a Graph Database for Semantic Literature-Based Discovery.

      Constructing a Graph Database for Semantic Literature-Based Discovery.

      Constructing a Graph Database for Semantic Literature-Based Discovery.

      Stud Health Technol Inform. 2015;216:1094

      Authors: Hristovski D, Kastrin A, Dinevski D, Rindflesch TC

      Abstract Literature-based discovery (LBD) generates discoveries, or hypotheses, by combining what is already known in the literature. Potential discoveries have the form of relations between biomedical concepts; for example, a drug may be determined to treat a disease other than the one for which it was intended.

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    10. Neural Discourse Relation Recognition with Semantic Memory. (arXiv:1603.03873v1 [cs.CL])

      Humans comprehend the meanings and relations of discourses heavily relying on their semantic memory that encodes general knowledge about concepts and facts. Inspired by this, we propose a neural recognizer for implicit discourse relation analysis, which builds upon a semantic memory that stores knowledge in a distributed fashion. We refer to this recognizer as SeMDER.

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    11. Methods and systems for ranking images using semantic and aesthetic models

      A method, a system, and a computer program product for extracting one or more images from a storage medium. A search model is selected based on the availability of a semantically related aesthetic model. A search model includes a generic aesthetic model if the semantically related aesthetic model for query is not available. A semantic score and an aesthetic score are computed based on the selected search model. The images are further ranked based on the semantic and aesthetic score.

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    12. Optimized Polynomial Evaluation with Semantic Annotations. (arXiv:1603.01520v1 [cs.PL])

      In this paper we discuss how semantic annotations can be used to introduce mathematical algorithmic information of the underlying imperative code to enable compilers to produce code transformations that will enable better performance. By using this approaches not only good performance is achieved, but also better programmability, maintainability and portability across different hardware architectures. To exemplify this we will use polynomial equations of different degrees.

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    13. Event Search and Analytics: Detecting Events in Semantically Annotated Corpora for Search and Analytics. (arXiv:1603.00260v1 [cs.IR])

      In this article, I present the questions that I seek to answer in my PhD research. I posit to analyze natural language text with the help of semantic annotations and mine important events for navigating large text corpora. Semantic annotations such as named entities, geographic locations, and temporal expressions can help us mine events from the given corpora. These events thus provide us with useful means to discover the locked knowledge in them.

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    14. Gibberish Semantics: How Good is Russian Twitter in Word Semantic Similarity Task?. (arXiv:1602.08741v1 [cs.CL])

      The most studied and most successful language models were developed and evaluated mainly for English and other close European languages, such as French, German, etc. It is important to study applicability of these models to other languages. The use of vector space models for Russian was recently studied for multiple corpora, such as Wikipedia, RuWac, lib.ru. These models were evaluated against word semantic similarity task.

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      Mentions: Russian
    15. Relationship information expansion apparatus, relationship information expansion method, and program

      A relationship information expansion apparatus capable of acquiring a new relationship based on a relationship information piece including two or more language expressions having a semantic relationship is provided. The relationship information expansion apparatus generates a candidate expanded relationship information piece in which at least one language expression included in the relationship information piece was replaced with a similar language expression, and acquires a score that indicates a probability that the candidate expanded relationship information piece has a semantic relationship. The relationship information expansion apparatus selects an expanded relationship information piece, which is a candidate expanded relationship information piece having ...

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    16. Sentence Similarity Learning by Lexical Decomposition and Composition. (arXiv:1602.07019v1 [cs.CL])

      Most conventional sentence similarity methods only focus on similar parts of two input sentences, and simply ignore the dissimilar parts, which usually give us some clues and semantic meanings about the sentences. In this work, we propose a model to take into account both the similarities and dissimilarities by decomposing and composing lexical semantics over sentences.

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    17. Semantic re-ranking of NLU results in conversational dialogue applications

      A human-machine dialog system is described which has multiple computer-implemented dialog components. A user client delivers output prompts to a human user and receives dialog inputs from the human user including speech inputs. An automatic speech recognition (ASR) engine processes the speech inputs to determine corresponding sequences of representative text words. A natural language understanding (NLU) engine processes the text words to determine corresponding NLU-ranked semantic interpretations. A semantic re-ranking module re-ranks the NLU-ranked semantic interpretations based on at least one of dialog context information and world knowledge information. A dialog manager responds to the re-ranked semantic interpretations and generates ...

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    18. Spatial Semantic Scan: Detecting Subtle, Spatially Localized Events in Text Streams. (arXiv:1511.00352v2 [cs.LG] UPDATED)

      Many methods have been proposed for detecting emerging events in text streams using topic modeling. However, these methods have shortcomings that make them unsuitable for rapid detection of locally emerging events on massive text streams. We describe Spatially Compact Semantic Scan (SCSS) that has been developed specifically to overcome the shortcomings of current methods in detecting new spatially compact events in text streams.

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    73-96 of 4027 « 1 2 3 4 5 6 7 ... 166 167 168 »
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