1. Articles in category: NER

    337-360 of 415 « 1 2 ... 12 13 14 15 16 17 18 »
    1. Formal Grammar for Hispanic Named Entities Analysis

      A task that has been widely studied in the field of natural language processing is the Named Entity Recognition (NER). A great number of approaches have been developed to deal with the identification and classification of named entity strings in specific- and open-domains. Nevertheless, external modules have to be incorporated into many of the NER systems in order to solve the interpretation problems derived from proper nouns. In this article our focus will be on the study of ambiguity in Hispanic Nominal Sequences which constitution assumes three main problems: (1) the association of given names and/or surnames; (2) the ...
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      Mentions: Mexico
    2. Extraction of CYP Chemical Interactions from Biomedical Literature Using Natural Language Processing Methods.

      Related Articles Extraction of CYP Chemical Interactions from Biomedical Literature Using Natural Language Processing Methods. J Chem Inf Model. 2009 Jan 21; Authors: Jiao D, Wild DJ This paper proposes a system that automatically extracts CYP protein and chemical interactions from journal article abstracts, using natural language processing (NLP) and text mining methods. In our system, we employ a maximum entropy based learning method, using results from syntactic, semantic, and lexical analysis of texts. We first present our system architecture and then discuss the data set for training our machine learning based models and the methods in building components in ...
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      Mentions: Indiana Bloomington
    3. Adaptive and scalable method for resolving natural language ambiguities

      A method for resolving ambiguities in natural language by organizing the task into multiple iterations of analysis done in successive levels of depth. The processing is adaptive to the users' need for accuracy and efficiency. At each level of processing the most accurate disambiguation is made based on the available information. As more analysis is done, additional knowledge is incorporated in a systematic manner to improve disambiguation accuracy. Associated with each level of processing is a measure of confidence, used to gauge the confidence of a process in its disambiguation accuracy. An overall confidence measure is also used to reflect ...
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    4. Challenges of Semantic Knowledge Management

      Forrester (Moore 2007) estimate that more than 80% of all corporate information is unstructured. Knowledge workers are increasingly overwhelmed by information from a bewildering array of information sources: emails, intranets, the web, etc. and yet still find it hard to access the specific information required for the task at hand. This implies that knowledge worker productivity is reduced and that organisations may be making decisions on the basis of incomplete knowledge. Furthermore, an inability to access key information can lead to compliance failure. As we have described in this volume, semantic technology is helping address these issues by associating unstructured ...
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      Mentions: John Davies
    5. Yowie: Information Extraction in a Service Enabled World

      Service Oriented Computing is a potential enabler for popular applications of Named Entity Recognition and Information Extraction. In this demo we show an example of such an application and discuss how Service Oriented Architecture (SOA) makes the application fully flexible and easily extensible. The application brings SOA close to the end-user and gives possibilities hardly possible with other approaches. Content Type Book ChapterDOI 10.1007/978-3-540-89652-4_68Authors Marek Kowalkiewicz, SAP Research 133 Mary Street Brisbane AustraliaKonrad Jünemann, SAP Research 133 Mary Street Brisbane Australia Book Series Lecture Notes in Computer ScienceOnline ISSN 1611-3349Print ISSN 0302-9743 Book Series Volume Volume 5364/2008 ...
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      Mentions: Brisbane
    6. Named Entity Recognition for Improving Retrieval and Translation of Chinese Documents

      This paper focuses on named entity recognition corresponding to people, organizations, locations, etc. in Chinese scientific documents. Two key benefits are shown by performing NER: (i) improved quality of semantic retrieval, and (ii) improvement in subsequent machine translation. Experiments using the Semantex platform for information extraction illustrate and quantify the two benefits outlined. Content Type Book ChapterDOI 10.1007/978-3-540-89533-6_56Authors Rohini K. Srihari, State University of New York at Buffalo Buffalo, NY USAErik Peterson, Janya Inc. Buffalo, NY USA Book Series Lecture Notes in Computer ScienceOnline ISSN 1611-3349Print ISSN 0302-9743 Book Series Volume Volume 5362/2008 Book Digital Libraries: Universal ...
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    7. Systems, methods and computer products for name disambiguation by using private/global directories, and communication contexts

      TRADEMARKSIBM.RTM. is a registered trademark of International Business Machines Corporation, Armonk, N.Y., U.S.A. Other names used herein may be registered trademarks, trademarks or product names of International Business Machines Corporation or othercompanies.BACKGROUND OF THE INVENTION1. Field of the InventionThis invention relates to name disambiguation, and particularly to systems, methods and computer products for name disambiguation by using private/global directories and communication con
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    8. Named Entity Recognition in Biomedical Literature: A Comparison of Support Vector Machines and Conditional Random Fields

      In this paper, we propose two named entity recognition systems for biomedical literature, System1 using support vector machines and System2 using conditional random fields. Through employing several sets of experiments, we make a comprehensive comparison between these two systems. The final results reflect that System2 can achieve higher accuracy than System1, because System2 can catch more essential properties by handling the richer set of features, i.e., adding not only the individual and dynamic features as System1 does but also the combinational features, which can improve the performance further. Furthermore, with carefully designed features, System2 can recognize named entities in ...
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    9. Spanish Nested Named Entity Recognition Using a Syntax-Dependent Tree Traversal-Based Strategy

      In this paper, we address the problem of nested Named Entity Recognition (NER) for Spanish. Phrase syntactic structure is exploited to generate a tree representation for the set of phrases that are candidate to be named entities. The classification of all candidate phrases is treated as a single problem, for which a globally optimal solution is approximated using a strategy based on the postorder traversal of that representation. Experimental results, obtained in the framework of SemEval 2007 Task 9 NER subtask, demonstrate the validity of our approach. Content Type Book ChapterDOI 10.1007/978-3-540-88636-5_13Authors Yunior Ramírez-Cruz, Universidad de Oriente Center ...
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    10. Mono-and Crosslingual Retrieval Experiments with Spatial Restrictions at GeoCLEF 2007

      The participation of the University of Hildesheim focused on the monolingual German and English tasks of GeoCLEF 2007. Based on the results of GeoCLEF 2005 and GeoCLEF 2006, the weighting and expansion of geographic Named Entities (NE) and Blind Relevance Feedback (BRF) were combined and an improved model for German Named Entity Recognition (NER) was evaluated. Post submission experiments are also presented.. A topic analysis revealed a wide spread of MAP values with high standard deviation values. Therefore further development will lie in the field of topic-adaptive systems. Content Type Book ChapterDOI 10.1007/978-3-540-85760-0_109Authors Ralph Kölle, University of Hildesheim ...
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    11. QA@L2F, First Steps at Qa@clef

      This paper presents QA@L2F, the question-answering system developed at L2F, INESC-ID. QA@L2F follows different strategies according with the question type, and relies strongly on named entity recognition and on the pre-detection of linguistic patterns. Each question type is mapped into a single strategy; however, if no answer is found, the system proceeds and tries to find an answer using one of the other strategies. Content Type Book ChapterDOI 10.1007/978-3-540-85760-0_45Authors Ana Mendes, L2F/INESC-ID Lisboa, Email: qa-clef@l2f.inesc-id.pt Rua Alves Redol, 9 1000-029 Lisboa PortugalLuísa Coheur, L2F/INESC-ID Lisboa, Email: qa-clef@l2f.inesc-id.pt Rua ...
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    12. What Happened to Esfinge in 2007?

      Esfinge is a general domain Portuguese question answering system which uses the information available on the Web as an additional resource when searching for answers. Other external resources and tools used are a broad coverage parser, a morphological analyser, a named entity recognizer and a Web-based database of word co-occurrences. In this fourth participation in CLEF, in addition to the new challenges posed by the organization (topics and anaphors in questions and the use of Wikipedia to search and support answers), we experimented with a multiple question and multiple answer approach in QA. Content Type Book ChapterDOI 10.1007/978-3-540-85760-0_31Authors ...
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      Mentions: Esfinge
    13. Bengali and Hindi to English CLIR Evaluation

      This paper presents a cross-language retrieval system for the retrieval of English documents in response to queries in Bengali and Hindi, as part of our participation in CLEF 2007 Ad-hoc bilingual track. We followed the dictionary-based Machine Translation approach to generate the equivalent English query out of Indian language topics. Our main challenge was to work with a limited coverage dictionary (of coverage ~ 20%) that was available for Hindi-English, and virtually non-existent dictionary for Bengali-English. So we depended mostly on a phonetic transliteration system to overcome this. The CLEF results point to the need for a rich bilingual lexicon, a ...
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      Mentions: India IIT Kharagpur
    14. Extracting and Querying Relations in Scientific Papers

      High-precision linguistic and semantic analysis of scientific texts is an emerging research area. We describe methods and an application for extracting interesting factual relations from scientific texts in computational linguistics and language technology. We use a hybrid NLP architecture with shallow preprocessing for increased robustness and domain-specific, ontology-based named entity recognition, followed by a deep HPSG parser running the English Resource Grammar (ERG). The extracted relations in the MRS (minimal recursion semantics) format are simplified and generalized using WordNet. The resulting ‘quriples’ are stored in a database from where they can be retrieved by relation-based search. The query interface is ...
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    15. Private Data Discovery for Privacy Compliance in Collaborative Environments

      With the growing use of computers and the Internet, it has become difficult for organizations to locate and effectively manage sensitive personally identifiable information (PII). This problem becomes even more evident in collaborative computing environments. PII may be hidden anywhere within the file system of a computer. As well, in the course of different activities, via collaboration or not, personally identifiable information may migrate from computer to computer. This makes meeting the organizational privacy requirements all the more complex. Our particular interest is to develop technology that would automatically discover workflow across organizational collaborators that would include private data. Since ...
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    16. Named Entity Recognition and Normalization: A Domain-Specific Language Approach

      We present, RNer, a tool that performs Named Entity Recognition and Normalization of gene and protein mentions on biomedical text. The tool we present not only offers a complete solution to the problem, but it does so by providing easily configurable framework, that abstracts the algorithmic details from the domain specific. Configuration and tuning for particular tasks is done using domain specific languages, clearer and more succinct, yet equally expressive that general purpose languages. An evaluation of the system is carried using the BioCreative datasets. Content Type Book ChapterDOI 10.1007/978-3-540-85861-4_18Authors Miguel Vazquez, Departamento de Ingeniería del Software e ...
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    17. Arabic Named Entity Recognition from Diverse Text Types

      Name identification has been worked on quite intensively for the past few years, and has been incorporated into several products. Many researchers have attacked this problem in a variety of languages but only a few limited researches have focused on Named Entity Recognition (NER) for Arabic text due to the lack of resources for Arabic named entities and the limited amount of progress made in Arabic natural language processing in general. In this paper, we present the results of our attempt at the recognition and extraction of 10 most important named entities in Arabic script; the person name, location, company ...
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    18. A Joint Segmenting and Labeling Approach for Chinese Lexical Analysis

      This paper introduces an approach which jointly performs a cascade of segmentation and labeling subtasks for Chinese lexical analysis, including word segmentation, named entity recognition and part-of-speech tagging. Unlike the traditional pipeline manner, the cascaded subtasks are conducted in a single step simultaneously, therefore error propagation could be avoided and the information could be shared among multi-level subtasks. In this approach, Weighted Finite State Transducers (WFSTs) are adopted. Within the unified framework of WFSTs, the models for each subtask are represented and then combined into a single one. Thereby, through one-pass decoding the joint optimal outputs for multi-level processes will ...
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    19. Hybrid apparatus for recognizing answer type

      BACKGROUND OF THE INVENTION1. Field of the InventionThe present invention relates to a hybrid apparatus for recognizing answer type, and more particularly, to a hybrid model and method for recognizing answer types in order to recognize a Korean answer type.2. Description of the Related ArtGenerally, a named entity recognition scheme extracts core information from a text and it is a necessary function to be included in a question and answer system or a text mining system. Particularly, a named en
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      Mentions: Korea lamda
    20. Extraction of semantic biomedical relations from text using conditional random fields.

      Related Articles Extraction of semantic biomedical relations from text using conditional random fields. BMC Bioinformatics. 2008;9:207 Authors: Bundschus M, Dejori M, Stetter M, Tresp V, Kriegel HP BACKGROUND: The increasing amount of published literature in biomedicine represents an immense source of knowledge, which can only efficiently be accessed by a new generation of automated information extraction tools. Named entity recognition of well-defined objects, such as genes or proteins, has achieved a sufficient level of maturity such that it can form the basis for the next step: the extraction of relations that exist between the recognized entities. Whereas most ...
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    21. Facilitating the development of controlled vocabularies for metabolomics technologies with text mining.

      Related Articles Facilitating the development of controlled vocabularies for metabolomics technologies with text mining. BMC Bioinformatics. 2008;9 Suppl 5:S5 Authors: Spasić I, Schober D, Sansone SA, Rebholz-Schuhmann D, Kell DB, Paton NW BACKGROUND: Many bioinformatics applications rely on controlled vocabularies or ontologies to consistently interpret and seamlessly integrate information scattered across public resources. Experimental data sets from metabolomics studies need to be integrated with one another, but also with data produced by other types of omics studies in the spirit of systems biology, hence the pressing need for vocabularies and ontologies in metabolomics. However, it is time-consuming and ...
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    22. Apparatus and method for recognizing biological named entity from biological literature based on UMLS

      BACKGROUND OF THE INVENTION1. Field of the InventionThe present invention relates to an apparatus and method for recognizing biological named entity from biological literature based on united medical language system (UMLS), in which the biological named entity is recognized and grouped.2. Description of the Related ArtAs the volume of biological literature is increased by active study on biology, also increased are demands for extraction of information from the literature at high quality. A prot
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      Mentions: Sophia Ananiadou
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