{"created":"2023-06-20T13:21:20.039346+00:00","id":1503,"links":{},"metadata":{"_buckets":{"deposit":"d54c7c88-27b4-4f84-85f5-14bbd2dc2199"},"_deposit":{"created_by":21,"id":"1503","owners":[21],"pid":{"revision_id":0,"type":"depid","value":"1503"},"status":"published"},"_oai":{"id":"oai:ir.soken.ac.jp:00001503","sets":["2:429:19"]},"author_link":["0","0","0"],"item_1_creator_2":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"McCRAE, John Philip"}],"nameIdentifiers":[{"nameIdentifier":"0","nameIdentifierScheme":"WEKO"}]}]},"item_1_creator_3":{"attribute_name":"フリガナ","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"マックレー, ジョン フィリップ"}],"nameIdentifiers":[{"nameIdentifier":"0","nameIdentifierScheme":"WEKO"}]}]},"item_1_date_granted_11":{"attribute_name":"学位授与年月日","attribute_value_mlt":[{"subitem_dategranted":"2009-09-30"}]},"item_1_degree_grantor_5":{"attribute_name":"学位授与機関","attribute_value_mlt":[{"subitem_degreegrantor":[{"subitem_degreegrantor_name":"総合研究大学院大学"}]}]},"item_1_degree_name_6":{"attribute_name":"学位名","attribute_value_mlt":[{"subitem_degreename":"博士（情報学）"}]},"item_1_description_12":{"attribute_name":"要旨","attribute_value_mlt":[{"subitem_description":"Ontologies provide a structured description of the concepts and terminology<br />used in a particular domain and provide valuable knowledge for a range of natu-<br />ral language processing applications. However, for many domains and languages<br />ontologies do not exist and manual creation is a difficult and resource-intensive<br />process. As such, automatic methods to extract, expand or aid the construction<br />of these resources is of significant interest.<br />　　There are a number of methods for extracting semantic information about<br />how terms are related from raw text, most notably the approach of Hearst<br />[1992], who used <i>patterns</i> to extract hypernym information. This method was<br />manual and it is not clear how to automatically generate patterns, which are<br />specific to a given relationship and domain. I present a novel method for de-<br />veloping patterns based on the use of alignments between patterns. Alignment<br />works well as it is closely related to the concept of a <i>join-set</i> of patterns, which<br />minimally generalise over-fitting patterns. I show that join-sets can be viewed<br />as an reduction on the search space of patterns, while resulting in no loss of<br />accuracy. I then show the results can be combined by a <i>support vector machine</i><br />to a obtain a classifier, which can decide if a pair of terms are related. I applied<br />this to several data sets and conclude that this method produces a precise result,<br />with reasonable recall.<br />　　The system I developed, like many semantic relation systems, produces only<br />a binary decision of whether a term pair is related. Ontologies have a structure,<br />that limits the forms of networks they represent. As the relation extraction is<br />generally noisy and incomplete, it is unlikely that the extracted relations will<br />match the structure of the ontology. As such I represent the structure of ontol-<br />ogy as a set of logical statements, and form a consistent ontology by finding the<br />network closest to the relation extraction system's output, which is consistent<br />with these restrictions. This gives a novel <i>NP-hard</i> optimisation problem, for<br />which I develop several algorithms. I present simple greedy approaches, and<br />branch and bound approaches, which my results show are not sufficient for this<br />problem. I then use resolution to show how this problem can be stated as an<br /><i>integer programming problem,</i> which can be efficiently solved by relaxing it to<br />a <i>linear programming problem</i>. I show that this result can efficiently solve the<br />problem, and furthermore when applied to the result of the relation extraction<br />system, this improves the quality of the extraction as well as converting it to an<br />ontological structure.","subitem_description_type":"Other"}]},"item_1_description_18":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_1_description_7":{"attribute_name":"学位記番号","attribute_value_mlt":[{"subitem_description":"総研大甲第1288号","subitem_description_type":"Other"}]},"item_1_select_14":{"attribute_name":"所蔵","attribute_value_mlt":[{"subitem_select_item":"有"}]},"item_1_select_8":{"attribute_name":"研究科","attribute_value_mlt":[{"subitem_select_item":"複合科学研究科"}]},"item_1_select_9":{"attribute_name":"専攻","attribute_value_mlt":[{"subitem_select_item":"17 情報学専攻"}]},"item_1_text_10":{"attribute_name":"学位授与年度","attribute_value_mlt":[{"subitem_text_value":"2009"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"McCRAE, John Philip","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"0","nameIdentifierScheme":"WEKO"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2016-02-17"}],"displaytype":"simple","filename":"甲1288_要旨.pdf","filesize":[{"value":"308.8 kB"}],"format":"application/pdf","licensetype":"license_11","mimetype":"application/pdf","url":{"label":"要旨・審査要旨","url":"https://ir.soken.ac.jp/record/1503/files/甲1288_要旨.pdf"},"version_id":"64906015-c777-4d0e-b4b3-d37598419d49"},{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2016-02-17"}],"displaytype":"simple","filename":"甲1288_本文.pdf","filesize":[{"value":"2.1 MB"}],"format":"application/pdf","licensetype":"license_11","mimetype":"application/pdf","url":{"label":"本文","url":"https://ir.soken.ac.jp/record/1503/files/甲1288_本文.pdf"},"version_id":"8bd3e0bc-a60c-4325-b10e-0407693bb186"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"thesis","resourceuri":"http://purl.org/coar/resource_type/c_46ec"}]},"item_title":"AUTOMATIC EXTRACTION OF LOGICALLY CONSISTENT ONTOLOGIES FROM TEXT CORPORA","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"AUTOMATIC EXTRACTION OF LOGICALLY CONSISTENT ONTOLOGIES FROM TEXT CORPORA"},{"subitem_title":"AUTOMATIC EXTRACTION OF LOGICALLY CONSISTENT ONTOLOGIES FROM TEXT CORPORA","subitem_title_language":"en"}]},"item_type_id":"1","owner":"21","path":["19"],"pubdate":{"attribute_name":"公開日","attribute_value":"2010-06-09"},"publish_date":"2010-06-09","publish_status":"0","recid":"1503","relation_version_is_last":true,"title":["AUTOMATIC EXTRACTION OF LOGICALLY CONSISTENT ONTOLOGIES FROM TEXT CORPORA"],"weko_creator_id":"21","weko_shared_id":-1},"updated":"2023-06-20T15:59:03.125008+00:00"}