1. Articles in category: NER

    337-360 of 381 « 1 2 ... 12 13 14 15 16 »
    1. Method and apparatus for implementing Q&A; function and computer-aided authoring

      The present invention provides a method for implementing Q&A; function for an electronic document, a method for computer-aided authoring, a method for browsing an electronic document, a computer-aided authoring apparatus, a browser capable of providing Q&A; function, a method for providing Q&A; service utilizing computers and a system for providing Q&A; service. Said method for implementing Q&A; function for an electronic document includes: when the writer is writing an electronic document, generating Q&A; information used for Q&A; function so that the reliability of the generated Q&A; information is ensured by the writer; saving said Q&A; information in correspondence with said ...
      Read Full Article
    2. Top 5 Natural Language Processing Applications

      In the last decades, Natural Language Processing (NLP) has been equally hyped and criticized. All in all, many applications emerged in the real world following intense and continued research and development. Here’s a list of the most prominent success stories. Given that this blog is about named entity recognition (NER), itself an NLP application, we would [...]
      Read Full Article
    3. Multi-class Named Entity Recognition Via Bootstrapping with Dependency Tree-Based Patterns

      Named Entity Recognition (NER) has become a well-known problem with many important applications, such as Question Answering, Relation Extraction and Concept Retrieval. NER based on unsupervised learning via bootstrapping is gaining researchers’ interest these days because it does not require manually annotating training data. Meanwhile, dependency tree-based patterns have proved to be effective in Relation Extraction. In this paper, we demonstrate that the use of dependency trees as extraction patterns, together with a bootstrapping framework, can improve the performance of the NER system and suggest a method for efficiently computing these tree patterns. Since unsupervised NER via bootstrapping uses the ...
      Read Full Article
      Mentions: Akiko Aizawa
    4. Chinese Organization Entity Recognition and Association on Web Pages

      In this paper, we consider the problem of automatic Chinese Named Entity Recognition (NER) on web pages and try to extract the association between recognized entities. Usually NER approaches mainly focus on plain text and get poor results on the Web pages of Internet. In this paper, we first explore the difference of plain texts and web pages for NER. Based on characteristic of HTML structure, we propose a set of unified methods to recognize and associate entities on web pages. In our experiments, the F-measure of organization name recognition is 73.6%, where 14.3% improvement is achieved beyond ...
      Read Full Article
    5. Pattern-Based Semantic Tagging for Ontology Population

      Ontology population has emerged as an increasingly important problem in semantic web services. In this paper, we propose a method using named entity recognition that extracts keywords from Web pages in order to populate a product ontology. The semantic classification determines meanings of terms and phrases by heuristic rules after the morphological analysis. In addition, our method classifies vocabularies into different semantic tags. Firstly, it records several lists of semantic tags to a history database. Then, we define some rules from the lists to extract a product name. Finally, the rules build and refine the product ontology semi-automatically. According to ...
      Read Full Article
    6. OSIRISv1.2: a named entity recognition system for sequence variants of genes in biomedical literature.

      Related Articles OSIRISv1.2: a named entity recognition system for sequence variants of genes in biomedical literature. BMC Bioinformatics. 2008;9:84 Authors: Furlong LI, Dach H, Hofmann-Apitius M, Sanz F BACKGROUND: Single Nucleotide Polymorphisms, among other type of sequence variants, constitute key elements in genetic epidemiology and pharmacogenomics. While sequence data about genetic variation is found at databases such as dbSNP, clues about the functional and phenotypic consequences of the variations are generally found in biomedical literature. The identification of the relevant documents and the extraction of the information from them are hampered by the large size of literature ...
      Read Full Article
    7. Product named entity recognition in Chinese text

      Abstract   There are many expressive and structural differences between product names and general named entities such as person names, location names and organization names. To date, there has been little research on product named entity recognition (NER), which is crucial and valuable for information extraction in the field of market intelligence. This paper focuses on product NER (PRO NER) in Chinese text. First, we describe our efforts on data annotation, including well-defined specifications, data analysis and development of a corpus with annotated product named entities. Second, a hierarchical hidden Markov model-based approach to PRO NER is proposed and evaluated. Extensive ...
      Read Full Article
    8. Natural Language Processing in aid of FlyBase curators.

      Related Articles Natural Language Processing in aid of FlyBase curators. BMC Bioinformatics. 2008 Apr 14;9(1):193 Authors: Karamanis N, Seal R, Lewin I, McQuilton P, Vlachos A, Gasperin C, Drysdale R, Briscoe T ABSTRACT: BACKGROUND: Despite increasing interest in applying Natural Language Processing (NLP) to biomedical text, whether this technology can facilitate tasks such as database curation remains unclear. RESULTS: PaperBrowser is the first NLP-powered interface that was developed under a user-centered approach to improve the way in which FlyBase curators navigate an article. In this paper, we first discuss how observing curators at work informed the design ...
      Read Full Article
    9. Cost-Effective Web Search in Bootstrapping for Named Entity Recognition

      In this paper, we propose a cost-effective search strategy framework to extract keywords in the same semantic class from the Web. Constructing a dictionary based on the bootstrapping technique is one promising approach to harnessing knowledge scattered around the Web. Open web application programming interfaces (APIs) are powerful tools for the knowledge-gathering process. However, we have to consider the cost of API calls because too many queries can overload the search engines, and they also limit the number of API calls. Our goal is to optimize a search strategy that can collect as many new words as possible with the ...
      Read Full Article
    10. Labeling Categories and Relationships in an Evolving Social Network

      Modeling and naming general entity-entity relationships is challenging in construction of social networks. Given a seed denoting a person name, we utilize Google search engine, NER (Named Entity Recognizer) parser, and CODC (Co-Occurrence Double Check) formula to construct an evolving social network. For each entity pair in the network, we try to label their categories and relationships. Firstly, we utilize an open directory project (ODP) resource, which is the largest human-edited directory of the web, to build a directed graph, and then use three ranking algorithms, PageRank, HITS, and a Markov chain random process to extract potential categories defined in ...
      Read Full Article
      Mentions: Markov Taipei Google
    11. An Executable Survey Of Advances In Biomedical Named Entity Recognition.

      Related Articles BANNER: an executable survey of advances in biomedical named entity recognition. Pac Symp Biocomput. 2008;:652-63 Authors: Leaman R, Gonzalez G There has been an increasing amount of research on biomedical named entity recognition, the most basic text extraction problem, resulting in significant progress by different research teams around the world. This has created a need for a freely-available, open source system implementing the advances described in the literature. In this paper we present BANNER, an open-source, executable survey of advances in biomedical named entity recognition, intended to serve as a benchmark for the field. BANNER is implemented ...
      Read Full Article
    12. NER Demos on the Web

      Here’s a list of demos for Named Entity Recognition technologies: YooName, this is our demo LingPipe, Alias-i Cognitive Computation Group, University of Illinois at Urbana-Champaign FreeLing, Open-Source Suite of Language Analyzers NET, University of Colorado POSBIOTM/W (biomedical), PosTech ClearForest, Reuters TriFeed, TriFeed Ltd. FactMine (for Dutch language), University of Groningen in The Netherlands Aventinus (for Swedish language), University of Gothenburg Natural [...]
      Read Full Article
    13. Classifier subset selection for biomedical named entity recognition

      Abstract  Classifier ensembling approach is considered for biomedical named entity recognition task. A vote-based classifier selection scheme having an intermediate level of search complexity between static classifier selection and real-valued and class-dependent weighting approaches is developed. Assuming that the reliability of the predictions of each classifier differs among classes, the proposed approach is based on selection of the classifiers by taking into account their individual votes. A wide set of classifiers, each based on a different set of features and modeling parameter setting are generated for this purpose. A genetic algorithm is developed so as to label the predictions of ...
      Read Full Article
    14. A web-based Bengali news corpus for named entity recognition

      Abstract  The rapid development of language resources and tools using machine learning techniques for less computerized languages requires appropriately tagged corpus. A tagged Bengali news corpus has been developed from the web archive of a widely read Bengali newspaper. A web crawler retrieves the web pages in Hyper Text Markup Language (HTML) format from the news archive. At present, the corpus contains approximately 34 million wordforms. Named Entity Recognition (NER) systems based on pattern based shallow parsing with or without using linguistic knowledge have been developed using a part of this corpus. The NER system that uses linguistic knowledge has ...
      Read Full Article
    15. What is a Named Entity?

      To our surprise, when it comes to defining the task of Named Entity Recognition (NER), nobody seems to question including temporal expressions and measures. This probably deserves some historic consideration, since the domain was popularized by information extraction competitions where, clearly, the date and the money generated by the event were crucial. But we receive [...]
      Read Full Article
      Mentions: London German Person
    16. Domain Information for Fine-Grained Person Name Categorization

      Named Entity Recognition became the basis of many Natural Language Processing applications. However, the existing coarse-grained named entity recognizers are insufficient for complex applications such as Question Answering, Internet Search engines or Ontology population. In this paper, we propose a domain distribution approach according to which names which occur in the same domains belong to the same fine-grained category. For our study, we generate a relevant domain resource by mapping and ranking the words from the WordNet glosses to their WordNetDomains. This approach allows us to capture the semantic information of the context around the named entity and thus to ...
      Read Full Article
    17. Kernel approaches for genic interaction extraction.

      Related Articles Kernel approaches for genic interaction extraction. Bioinformatics. 2008 Jan 1;24(1):118-26 Authors: Kim S, Yoon J, Yang J MOTIVATION: Automatic knowledge discovery and efficient information access such as named entity recognition and relation extraction between entities have recently become critical issues in the biomedical literature. However, the inherent difficulty of the relation extraction task, mainly caused by the diversity of natural language, is further compounded in the biomedical domain because biomedical sentences are commonly long and complex. In addition, relation extraction often involves modeling long range dependencies, discontiguous word patterns and semantic relations for which the ...
      Read Full Article
    18. Semantic taxonomy induction from heterogenous evidence

      Semantic Taxonomy Induction from Heterogenous Evidence Rion Snow Computer Science Department Stanford University Stanford, CA 94305 rion@cs.stanford.edu Daniel Jurafsky Linguistics Department Stanford University Stanford, CA 94305 jurafsky@stanford.edu Andrew Y. Ng Computer Science Department Stanford University Stanford, CA 94305 ang@cs.stanford.edu Abstract We propose a novel algorithm for inducing semantic taxonomies. Previous algorithms for taxonomy induction have typically focused on ind
      Read Full Article
    19. Named entity (NE) interface for multiple client application programs

      The present invention is a named entity (NE) interface to a linguistic analysis layer. The interface exposes each input sentence to the NE recognizers of all applications and returns all recognized NEs. Thus, the present invention can accommodate NEs which dynamically change in the applications, because each input string will be handed to the applications for NE recognition. The present invention also includes a data structure which is a normalized form of recognized NEs.
      Read Full Article
    20. Ranking Algorithms for Named-Entity Extraction: Boosting and theVoted Perceptron.

      Ranking Algorithms for Named--Entity Extraction: Boosting and the Voted Perceptron Michael Collins AT&T Labs-Research, Florham Park, New Jersey. mcollins@research.att.com Abstract This paper describes algorithms which rerank the top N hypotheses from a maximum-entropy tagger, the application being the recovery of named-entity boundaries in a corpus of web data. The first approach uses a boosting algorithm for ranking problems. The second approach uses the voted perceptron algorithm. Both algorit
      Read Full Article
    21. Machine Learning Methods in Natural Language Processing

      Machine Learning Methods in Natural Language Processing Michael Collins MIT CSAIL Some NLP Problems Information extraction – Named entities – Relationships between entities Finding linguistic structure – Part-of-speech tagging – Parsing Machine translation Common Themes Need to learn mapping from one discrete structure to another – Strings to hidden state sequences Named-entity extraction, part-of-speech tagging – Strings to strings Machine translation – Strings to underlying trees Pa
      Read Full Article
    22. Discriminative Reranking for Natural Language Parsing.

      Discriminative Reranking for Natural Language Parsing Michael Collins and Terry Koo Massachusetts Institute of Technology This paper considers approaches which rerank the output of an existing probabilistic parser. The base parser produces a set of candidate parses for each input sentence, with associated probabilities that de ne an initial ranking of these parses. A second model then attempts to improve upon this initial ranking, using additional features of the tree as evidence. The strength
      Read Full Article
    337-360 of 381 « 1 2 ... 12 13 14 15 16 »
  1. Categories

    1. Default:

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

  3. Organizations in the News

    1. (2 articles) NLP
    2. (2 articles) NER
    3. (2 articles) BMC Med Inform Decis Mak
    4. (2 articles) POS
    5. (1 articles) European Union
    6. (1 articles) API
    7. (1 articles) Markov
    8. (1 articles) ICT
    9. (1 articles) Genia
    10. (1 articles) Sbar
    11. (1 articles) Faculty of Mathematics
    12. (1 articles) RDF
  4. Locations in the News

    1. (1 articles) Slovenia
    2. (1 articles) Ljubljana
  5. People in the News

    1. (1 articles) Jozef Stefan Institute
    2. (1 articles) Denny JC