1. Articles in category: Semantic

    73-96 of 4040 « 1 2 3 4 5 6 7 ... 167 168 169 »
    1. Neural Semantic Role Labeling with Dependency Path Embeddings. (arXiv:1605.07515v1 [cs.CL])

      This paper introduces a novel model for semantic role labeling that makes use of neural sequence modeling techniques. Our approach is motivated by the observation that complex syntactic structures and related phenomena, such as nested subordinations and nominal predicates, are not handled well by existing models. Our model treats such instances as sub-sequences of lexicalized dependency paths and learns suitable embedding representations.

      Read Full Article
    2. New cybersecurity technique uses semantic gaps to detect website promotional attacks

      New cybersecurity technique uses semantic gaps to detect website promotional attacks

      Science | | Researchers have developed a new cybersecurity technique, known as Semantic Inconsistency Search (SEISE), that uses natural language processing to spot the differences between a compromised site’s expected content and malicious advertising and promotional code, often a sign of attacks that install malware or drive traffic to websites hosting illegal commerce. Full story at

      Read Full Article
    3. Acquisition of semantic class lexicons for query tagging

      A user's search experience may be enhanced by providing additional content based upon an understanding of the user's intent. Query tagging, the assigning of semantic labels to terms within a query, is one technique that may be utilized to determine the context of a user's search query. Accordingly, as provided herein, a query tagging model may be updated using one or more stratified lexicons. A list data structure (e.g., lists of phrases obtained from web pages) and seed distribution data (e.g., pre-labeled probability data) may be used by a graph learning technique to obtain an ...

      Read Full Article
    4. Ontology-based annotations and semantic relations in large-scale (epi)genomics data.

      Ontology-based annotations and semantic relations in large-scale (epi)genomics data.

      Ontology-based annotations and semantic relations in large-scale (epi)genomics data.

      Brief Bioinform. 2016 May 3;

      Authors: Galeota E, Pelizzola M

      Abstract Public repositories of large-scale biological data currently contain hundreds of thousands of experiments, including high-throughput sequencing and microarray data. The potential of using these resources to assemble data sets combining samples previously not associated is vastly unexplored.

      Read Full Article
    5. IISCNLP at SemEval-2016 Task 2: Interpretable STS with ILP based Multiple Chunk Aligner. (arXiv:1605.01194v1 [cs.CL])

      Interpretable semantic textual similarity (iSTS) task adds a crucial explanatory layer to pairwise sentence similarity. We address various components of this task: chunk level semantic alignment along with assignment of similarity type and score for aligned chunks with a novel system presented in this paper. We propose an algorithm, iMATCH, for the alignment of multiple non-contiguous chunks based on Integer Linear Programming (ILP).

      Read Full Article
    6. Exploiting Deep Semantics and Compositionality of Natural Language for Human-Robot-Interaction. (arXiv:1604.06721v1 [cs.AI])

      We develop a natural language interface for human robot interaction that implements reasoning about deep semantics in natural language. To realize the required deep analysis, we employ methods from cognitive linguistics, namely the modular and compositional framework of Embodied Construction Grammar (ECG) [Feldman, 2009]. Using ECG, robots are able to solve fine-grained reference resolution problems and other issues related to deep semantics and compositionality of natural language.

      Read Full Article
    7. A high throughput semantic concept frequency based approach for patient identification: a case study using type 2 diabetes mellitus clinical notes.

      A high throughput semantic concept frequency based approach for patient identification: a case study using type 2 diabetes mellitus clinical notes.

      A high throughput semantic concept frequency based approach for patient identification: a case study using type 2 diabetes mellitus clinical notes.

      AMIA Annu Symp Proc. 2010;2010:857-61

      Authors: Wei WQ, Tao C, Jiang G, Chute CG

      Abstract UNLABELLED: Current research on high throughput identification of patients with a specific phenotype is in its infancy. There is an urgent need to develop a general automatic approach for patient identification.

      Read Full Article
    8. Predicting Lexical Relations between Biomedical Terms: towards a Multilingual Morphosemantics-based System.

      Predicting Lexical Relations between Biomedical Terms: towards a Multilingual Morphosemantics-based System.

      Predicting Lexical Relations between Biomedical Terms: towards a Multilingual Morphosemantics-based System.

      Stud Health Technol Inform. 2005;116:793-8

      Authors: Namer F, Baud R

      Abstract This paper addresses the issue of how semantic information can be automatically assigned to compound terms, i.e. both a definition and a set of semantic relations. This issue is particularly crucial when elaborating multilingual databases and when developing cross-language information retrieval systems.

      Read Full Article
    9. A Process for the Representation of openEHR ADL Archetypes in OWL Ontologies.

      A Process for the Representation of openEHR ADL Archetypes in OWL Ontologies.

      A Process for the Representation of openEHR ADL Archetypes in OWL Ontologies.

      Stud Health Technol Inform. 2015;216:827-31

      Authors: Porn AM, Peres LM, Didonet Del Fabro M

      Abstract ADL is a formal language to express archetypes, independent of standards or domain. However, its specification is not precise enough in relation to the specialization and semantic of archetypes, presenting difficulties in implementation and a few available tools.

      Read Full Article
    10. Semantic search by means of word sense disambiguation using a lexicon

      Techniques are disclosed for analyzing a "context window" of a search query to determine a semantic meaning of a search word and to filter search results based upon the semantic meaning. Generally, a lexicon may be used to store forms, meanings, and usages of words and phrases. When a user specifies a query, a semantic analyzer obtains all of the word senses for a search word. The semantic analyzer applies lexical analysis techniques to the search word and context window to obtain a total score for each word sense and selects the word sense with the highest total score. After ...

      Read Full Article
    11. 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.

      Read Full Article
    12. 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.

      Read Full Article
    13. 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.

      Read Full Article
    14. 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 ...

      Read Full Article
    15. 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.

      Read Full Article
    16. 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.

      Read Full Article
    17. 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.

      Read Full Article
    73-96 of 4040 « 1 2 3 4 5 6 7 ... 167 168 169 »
  1. Categories

    1. Default:

      Discourse, Entailment, Machine Translation, NER, Parsing, Segmentation, Semantic, Sentiment, Summarization, WSD
  2. Popular Articles

  3. Organizations in the News

    1. (3 articles) Stud Health Technol Inform
    2. (2 articles) NLP
    3. (1 articles) Google
    4. (1 articles) Stanford
    5. (1 articles) Hannover Medical School
    6. (1 articles) Linguistic Systems, Inc.
    7. (1 articles) IAA
  4. Locations in the News

    1. (1 articles) Bayes