Enhancement of Chemical Entity Identification in Text Using Semantic Similarity Validation
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{"title"=>"Enhancement of Chemical Entity Identification in Text Using Semantic Similarity Validation", "type"=>"journal", "authors"=>[{"first_name"=>"Tiago", "last_name"=>"Grego", "scopus_author_id"=>"15753437800"}, {"first_name"=>"Francisco M.", "last_name"=>"Couto", "scopus_author_id"=>"6603489917"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84877045484", "sgr"=>"84877045484", "pui"=>"368847543", "isbn"=>"10.1371/journal.pone.0062984", "pmid"=>"23658791", "doi"=>"10.1371/journal.pone.0062984"}, "id"=>"3c8f9d32-283f-399f-870f-76573330377d", "abstract"=>"With the amount of chemical data being produced and reported in the literature growing at a fast pace, it is increasingly important to efficiently retrieve this information. To tackle this issue text mining tools have been applied, but despite their good performance they still provide many errors that we believe can be filtered by using semantic similarity. Thus, this paper proposes a novel method that receives the results of chemical entity identification systems, such as Whatizit, and exploits the semantic relationships in ChEBI to measure the similarity between the entities found in the text. The method assigns a single validation score to each entity based on its similarities with the other entities also identified in the text. Then, by using a given threshold, the method selects a set of validated entities and a set of outlier entities. We evaluated our method using the results of two state-of-the-art chemical entity identification tools, three semantic similarity measures and two text window sizes. The method was able to increase precision without filtering a significant number of correctly identified entities. This means that the method can effectively discriminate the correctly identified chemical entities, while discarding a significant number of identification errors. For example, selecting a validation set with 75% of all identified entities, we were able to increase the precision by 28% for one of the chemical entity identification tools (Whatizit), maintaining in that subset 97% the correctly identified entities. Our method can be directly used as an add-on by any state-of-the-art entity identification tool that provides mappings to a database, in order to improve their results. The proposed method is included in a freely accessible web tool at www.lasige.di.fc.ul.pt/webtools/ice/.", "link"=>"http://www.mendeley.com/research/enhancement-chemical-entity-identification-text-using-semantic-similarity-validation", "reader_count"=>18, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>2, "Researcher"=>5, "Student > Ph. D. Student"=>4, "Student > Master"=>5, "Other"=>1, "Professor"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>2, "Researcher"=>5, "Student > Ph. D. Student"=>4, "Student > Master"=>5, "Other"=>1, "Professor"=>1}, "reader_count_by_subject_area"=>{"Biochemistry, Genetics and Molecular Biology"=>1, "Agricultural and Biological Sciences"=>4, "Veterinary Science and Veterinary Medicine"=>1, "Chemistry"=>2, "Computer Science"=>10}, "reader_count_by_subdiscipline"=>{"Chemistry"=>{"Chemistry"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>4}, "Computer Science"=>{"Computer Science"=>10}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "reader_count_by_country"=>{"United States"=>2, "Brazil"=>1, "United Kingdom"=>1, "Portugal"=>2, "Spain"=>2}, "group_count"=>0}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1052364"], "description"=>"<p>Results of entity identification (recognition and resolution to ChEBI) obtained by the two used tools in the patent corpus. An exact matching assessment was considered. Annotations indicate the total amount of entities recognized, TP indicates how many were in accordance to the gold standard.</p>", "links"=>[], "tags"=>["Computational biology", "bio-ontologies", "Natural Language Processing", "text mining", "Computer applications", "Web-based applications", "Information technology", "databases", "signal processing", "data mining"], "article_id"=>696832, "categories"=>["Information And Computing Sciences", "Engineering", "Chemistry", "Biological Sciences"], "users"=>["Tiago Grego", "Francisco M. Couto"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0062984.t001", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Automatic_entity_identification_results_/696832", "title"=>"Automatic entity identification results.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-05-02 01:53:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/1052362"], "description"=>"<p>For selected subsets of validated entities corresponding to 25%, 50% and 75% of the total amount on annotations performed by each tool (Method), we present the True Positive ratio (TP Ratio), which corresponds to the percentage of True Positives remaining in the subset, and the Precision increase relative to the Precision for the total amount on annotations (P Increase). For this evaluation was used the document-wide as text window.</p>", "links"=>[], "tags"=>["Computational biology", "bio-ontologies", "Natural Language Processing", "text mining", "Computer applications", "Web-based applications", "Information technology", "databases", "signal processing", "data mining", "validation"], "article_id"=>696830, "categories"=>["Information And Computing Sciences", "Engineering", "Chemistry", "Biological Sciences"], "users"=>["Tiago Grego", "Francisco M. Couto"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0062984.t003", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Relative_validation_results_using_the_document_as_text_window_/696830", "title"=>"Relative validation results, using the document as text window.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-05-02 01:53:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/1052353"], "description"=>"<p>Shows the variation in precision and recall with the validation score threshold, using the Resnik measure with a document as text window. Straight dots represent the expected behavior of a random validation system.</p>", "links"=>[], "tags"=>["Computational biology", "bio-ontologies", "Natural Language Processing", "text mining", "Computer applications", "Web-based applications", "Information technology", "databases", "signal processing", "data mining", "crf-based", "annotation"], "article_id"=>696826, "categories"=>["Information And Computing Sciences", "Engineering", "Chemistry", "Biological Sciences"], "users"=>["Tiago Grego", "Francisco M. Couto"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0062984.g002", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Validation_of_CRF_based_annotation_results_/696826", "title"=>"Validation of CRF-based annotation results.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-05-02 01:53:46"}
  • {"files"=>["https://ndownloader.figshare.com/files/1052359"], "description"=>"<p>Our validation method was implemented in a web tool containing the CRF-based chemical identification method. A sample sentence from patent document WO2007041564 is shown with some chemical entities, and their validation score. Validated entities (validation score above the defined validation threshold, selected in this example as 75%) are presented in green, while outliers are presented in yellow.</p>", "links"=>[], "tags"=>["Computational biology", "bio-ontologies", "Natural Language Processing", "text mining", "Computer applications", "Web-based applications", "Information technology", "databases", "signal processing", "data mining"], "article_id"=>696829, "categories"=>["Information And Computing Sciences", "Engineering", "Chemistry", "Biological Sciences"], "users"=>["Tiago Grego", "Francisco M. Couto"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0062984.g004", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Web_tool_screenshot_/696829", "title"=>"Web tool screenshot.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-05-02 01:53:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1052355"], "description"=>"<p>Boxplot of the validation score obtained for the manual annotations in the gold standard, and the automatic annotations provided by the dictionary-based method and the CRF-based method.</p>", "links"=>[], "tags"=>["Computational biology", "bio-ontologies", "Natural Language Processing", "text mining", "Computer applications", "Web-based applications", "Information technology", "databases", "signal processing", "data mining", "validation"], "article_id"=>696828, "categories"=>["Information And Computing Sciences", "Engineering", "Chemistry", "Biological Sciences"], "users"=>["Tiago Grego", "Francisco M. Couto"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0062984.g003", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_the_validation_scores_/696828", "title"=>"Comparison of the validation scores.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-05-02 01:53:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/1052352"], "description"=>"<p>Shows the variation in precision and recall with the validation score threshold, using the Resnik measure with a document as text window. Straight dots represent the expected behavior of a random validation system.</p>", "links"=>[], "tags"=>["Computational biology", "bio-ontologies", "Natural Language Processing", "text mining", "Computer applications", "Web-based applications", "Information technology", "databases", "signal processing", "data mining", "whatizit", "annotation"], "article_id"=>696825, "categories"=>["Information And Computing Sciences", "Engineering", "Chemistry", "Biological Sciences"], "users"=>["Tiago Grego", "Francisco M. Couto"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0062984.g001", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Validation_of_Whatizit_annotation_results_/696825", "title"=>"Validation of Whatizit annotation results.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-05-02 01:53:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/1052365"], "description"=>"<p>Amount of True Positives (TP) and Precision obtained at selected subsets of validated entities corresponding to 25%, 50% and 75% of the total amount on annotations performed by each tool (Method), using validation calculated using the semantic similarity measure indicated in Measure. The text window used for this evaluation was a paragraph-wide text window.</p>", "links"=>[], "tags"=>["Computational biology", "bio-ontologies", "Natural Language Processing", "text mining", "Computer applications", "Web-based applications", "Information technology", "databases", "signal processing", "data mining", "paragraph"], "article_id"=>696833, "categories"=>["Information And Computing Sciences", "Engineering", "Chemistry", "Biological Sciences"], "users"=>["Tiago Grego", "Francisco M. Couto"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0062984.t004", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Validation_results_using_the_paragraph_as_text_window_/696833", "title"=>"Validation results, using the paragraph as text window.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-05-02 01:53:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/1052363"], "description"=>"<p>Amount of True Positives (TP) and Precision obtained at selected subsets of validated entities corresponding to 25%, 50% and 75% of the total amount on annotations performed by each tool (Method), using validation calculated using the semantic similarity measure indicated in Measure. For this evaluation was used the document-wide as text window.</p>", "links"=>[], "tags"=>["Computational biology", "bio-ontologies", "Natural Language Processing", "text mining", "Computer applications", "Web-based applications", "Information technology", "databases", "signal processing", "data mining"], "article_id"=>696831, "categories"=>["Information And Computing Sciences", "Engineering", "Chemistry", "Biological Sciences"], "users"=>["Tiago Grego", "Francisco M. Couto"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0062984.t002", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Validation_results_using_the_document_as_text_window_/696831", "title"=>"Validation results, using the document as text window.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-05-02 01:53:51"}

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Relative Metric

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