1. Articles in category: NER

    313-336 of 381 « 1 2 ... 11 12 13 14 15 16 »
    1. 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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    2. 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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    3. 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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    4. 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
    5. 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
    6. 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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    7. 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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    8. 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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    9. 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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    10. 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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    11. 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
    12. 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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    13. 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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    14. 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
    15. Systems and methods for using and constructing user-interest sensitive indicators of search results

      INCORPORATION BY REFERENCEThe following co-pending application:"Systems and Methods for User-Interest Sensitive Note-Taking" by R. KAPLAN et al., filed Nov. 30, 2004, as U.S. application Ser. No. 10/999,793, and published as U.S. Publication No. 2006/0116861A1 on June 1, 2006; and"Systems and Methods for User-Interest Sensitive Condensation" by R. KAPLAN et al., filed Nov. 30, 2004, as U.S. application Ser. No. 10/999,792, and published as U.S. Publication No. 2006/0116860A1 on June 1,2006;"Syst
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    16. Supporting Named Entity Recognition and Syntactic Analysis with Full-Text Queries

      JaTeDigo is a natural language interface (in Portuguese) to a cinema database that has to deal with a vocabulary of more than 2500000 movies, actors and staff names. As our tools were not able to deal with such a huge amount of information, we decided to profit from full-text queries to the database to support named entity recognition (NER) and syntactic analysis of questions. This paper describes this methodology and evaluates it within JaTeDigo. Content Type Book ChapterDOI 10.1007/978-3-540-69858-6_38Authors Luísa Coheur, L2F/INESC-ID Lisboa Rua Alves Redol, 9 1000-029 Lisboa PortugalAna Guimarães, L2F/INESC-ID Lisboa Rua Alves Redol ...
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      Mentions: Rua Alves Redol
    17. Enhanced Services for Targeted Information Retrieval by Event Extraction and Data Mining

      We present a framework combining information retrieval with machine learning and (pre-)processing for named entity recognition in order to extract events from a large document collection. The extracted events become input to a data mining component which delivers the final output to specific user’s questions. Our case study is the public collection of minutes of plenary sessions of the German parliament and of petitions to the German parliament. Content Type Book ChapterDOI 10.1007/978-3-540-69858-6_36Authors Felix Jungermann, TU Dortmund Artificial Intelligence UnitKatharina Morik, TU Dortmund Artificial Intelligence Unit Book Series Lecture Notes in Computer ScienceOnline ISSN 1611-3349Print ISSN ...
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    18. A de-identifier for medical discharge summaries.

      Related Articles A de-identifier for medical discharge summaries. Artif Intell Med. 2008 Jan;42(1):13-35 Authors: Uzuner O, Sibanda TC, Luo Y, Szolovits P OBJECTIVE: Clinical records contain significant medical information that can be useful to researchers in various disciplines. However, these records also contain personal health information (PHI) whose presence limits the use of the records outside of hospitals. The goal of de-identification is to remove all PHI from clinical records. This is a challenging task because many records contain foreign and misspelled PHI; they also contain PHI that are ambiguous with non-PHI. These complications are compounded by ...
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    19. Document anonymization apparatus and method

      Named entities in a document are identified. Each named entity is classified as either anonymous or public based on analysis including at least syntactic analysis of one or more portions of the document containing the named entity. In one suitable approach, each named person entity is classified by default as anonymous, and each named entity that is not a named person is classified by default as public. Named entities are selectively re-classified based on evidence contained in the document indicating that the default classification is incorrect. The classification of a named entity as either anonymous or public is propagated to ...
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      Mentions: Japan Tokyo Canada
    20. A common sense geographic knowledge base for GIR

      Abstract  As background knowledge of geographic information retrieval (GIR), the gazetteers have their limitations. In this paper we propose to develop and implement a common sense geographic knowledge base (CSGKB) instead of the gazetteers. We define that CSGKB is concerned with the representation of geographic knowledge in human brain and the simulation of geographic reasoning in daily life. Traditional geographic information system (GIS) is based on the model of map with its data based on geographic coordinates and its computation based on geometry. However, CSGKB, which is made up of geographic features and relationships and is based on qualitative spatio-temporal ...
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    21. Assessment of disease named entity recognition on a corpus of annotated sentences.

      Related Articles Assessment of disease named entity recognition on a corpus of annotated sentences. BMC Bioinformatics. 2008;9 Suppl 3:S3 Authors: Jimeno A, Jimenez-Ruiz E, Lee V, Gaudan S, Berlanga R, Rebholz-Schuhmann D BACKGROUND: In recent years, the recognition of semantic types from the biomedical scientific literature has been focused on named entities like protein and gene names (PGNs) and gene ontology terms (GO terms). Other semantic types like diseases have not received the same level of attention. Different solutions have been proposed to identify disease named entities in the scientific literature. While matching the terminology with language patterns ...
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    22. Fusion of Multiple Features for Chinese Named Entity Recognition Based on CRF Model

      This paper presents the ability of Conditional Random Field (CRF) combining with multiple features to perform robust and accurate Chinese Named Entity Recognition. We describe the multiple feature templates including local feature templates and global feature templates used to extract multiple features with the help of human knowledge. Besides, we show that human knowledge can reasonably smooth the model and thus the need of training data for CRF might be reduced. From the experimental results on People’s Daily corpus, we can conclude that our model is an effective pattern to combine statistical model and human knowledge. And the experiments ...
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    23. Semi-joint Labeling for Chinese Named Entity Recognition

      Named entity recognition (NER) is an essential component of text mining applications. In Chinese sentences, words do not have delimiters; thus, incorporating word segmentation information into an NER model can improve its performance. Based on the framework of dynamic conditional random fields, we propose a novel labeling format, called semi-joint labeling which partially integrates word segmentation information and named entity tags for NER. The model enhances the interaction of segmentation tags and NER achieved by traditional approaches. Moreover, it allows us to consider interactions between multiple chains in a linear-chain model. We use data from the SIGHAN 2006 NER bakeoff ...
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      Mentions: Taipei Taiwan Hsinchu
    24. Recognizing Biomedical Named Entities in Chinese Research Abstracts

      Most research on biomedical named entity recognition has focused on English texts, e.g., MEDLINE abstracts. However, recent years have also seen significant growth of biomedical publications in other languages. For example, the Chinese Biomedical Bibliographic Database has collected over 3 million articles published after 1978 from 1600 Chinese biomedical journals. We present here a Conditional Random Field (CRF) based system for recognizing biomedical named entities in Chinese texts. Viewing Chinese sentences as sequences of characters, we trained and tested the CRF model using a manually annotated corpus containing 106 research abstracts (481 sentences in total). The features we used ...
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    313-336 of 381 « 1 2 ... 11 12 13 14 15 16 »
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