{"_buckets": {"deposit": "cf0559ed-e04d-45d4-b009-1b034eec2556"}, "_deposit": {"created_by": 27, "id": "1928", "owners": [27], "pid": {"revision_id": 0, "type": "depid", "value": "1928"}, "status": "published"}, "_oai": {"id": "oai:repo.lib.tut.ac.jp:00001928", "sets": ["9"]}, "author_link": ["3722", "3721", "2102", "1945", "3724", "3336", "3723"], "item_10001_biblio_info_7": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2015-12-28", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "4", "bibliographicPageEnd": "26", "bibliographicPageStart": "16", "bibliographicVolumeNumber": "8", "bibliographic_titles": [{"bibliographic_title": "情報処理学会論文誌(トランザクション）データベース（TOD）"}]}]}, "item_10001_description_5": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "ツイートに含まれる特徴と位置情報を対応させることで，実世界を観測するセンサとしてTwitterを活用することができる．しかし位置情報が付加されたツイートは少なく，Twitterをセンサとして活用するときの問題の1つとなる．そこで本研究では，ツイートの投稿位置を推定し，より多くのツイートに正確な位置情報を付与することを目的とする．この目的を達成するために，ツイート中のノイズとなる単語を除去するためのフィルタリング手法を提案する．また，単語の地理的分布を平滑化するためのスムージング手法も提案する．これらの提案手法が従来手法よりも有効に機能することを示し，その考察を行う．\nTwitter can be considered as a real-time sensor that responds to real-world events by combining the content and location information of tweets. However, a problem persists: tweets containing location information are too small. To overcome this problem, we estimate the location where a tweet was posted. Our main method involves using word filters called AF filter and TF-IAF filter that detect stop words. In addition, we propose a smoothing method called Distance smoothing for overcoming sparsity of words. We show that both our methods improve location estimation accuracy and discuss the features of the results.  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"subitem_subject_scheme": "Other"}, {"subitem_subject": "ノイズ除去", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Twitter", "subitem_subject_language": "en", "subitem_subject_scheme": "Other"}, {"subitem_subject": "geo-location estimation", "subitem_subject_language": "en", "subitem_subject_scheme": "Other"}, {"subitem_subject": "stop word detection", "subitem_subject_language": "en", "subitem_subject_scheme": "Other"}]}, "item_language": {"attribute_name": "言語", "attribute_value_mlt": [{"subitem_language": "jpn"}]}, "item_resource_type": {"attribute_name": "資源タイプ", "attribute_value_mlt": [{"resourcetype": "journal article", "resourceuri": "http://purl.org/coar/resource_type/c_6501"}]}, "item_title": "ツイート投稿位置推定のための単語フィルタリング手法", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "ツイート投稿位置推定のための単語フィルタリング手法"}, {"subitem_title": "Geo-location Estimation of Tweets with Stop Words Detection", "subitem_title_language": "en"}]}, "item_type_id": 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