{"created":"2021-03-01T07:02:39.531711+00:00","id":42731,"links":{},"metadata":{"_buckets":{"deposit":"564c1e8f-3065-400e-8cdd-fc17ea007510"},"_deposit":{"id":"42731","owners":[],"pid":{"revision_id":0,"type":"depid","value":"42731"},"status":"published"},"_oai":{"id":"oai:repository.dl.itc.u-tokyo.ac.jp:00042731","sets":["62:7433:7434","9:7435:7436"]},"item_8_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2003-02","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2003-CF-194","bibliographic_titles":[{"bibliographic_title":"Discussion paper series. CIRJE-F"}]}]},"item_8_description_13":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_8_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Utilizing data from a log file, a two-stage model for step-ahead web page prediction that permits adaptive page customization in real-time is proposed. The first stage predicts the next page of a viewer based on a variant of a Markov transition matrix computed from page sequences of other visitors who read the same pages as that viewer did thus far. The second stage re-analyzes the incorrect exit/continuation predictions of the first stage through data mining, incorporating the visitor's viewing behavior observed from the log file. The two-stage process takes advantage of a robust, theory-driven nature of statistical modeling for extracting the overall feature of the data, and a flexible, data-driven nature of data mining to capture any idiosyncrasies and complications unresolved in the first stage. The empirical result with a test site implies that the first stage alone is sufficiently accurate (50.3%) in predicting page transitions. Prediction of site exit was even better with 100% of the exit and 90.8% of the continuation predictions being correct. The result was compared against other models for predictive accuracy.","subitem_description_type":"Abstract"}]},"item_8_description_6":{"attribute_name":"内容記述","attribute_value_mlt":[{"subitem_description":"International Journal of Electronic Business. 掲載予定.","subitem_description_type":"Other"},{"subitem_description":"本文フィルはリンク先を参照のこと","subitem_description_type":"Other"}]},"item_8_publisher_20":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"日本経済国際共同センター"}]},"item_8_relation_25":{"attribute_name":"関係URI","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_id_text":"http://www.cirje.e.u-tokyo.ac.jp/research/dp/2003/2003cf194ab.html","subitem_relation_type_select":"URI"}}]},"item_8_source_id_10":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11450569","subitem_source_identifier_type":"NCID"}]},"item_8_subject_15":{"attribute_name":"日本十進分類法","attribute_value_mlt":[{"subitem_subject":"330","subitem_subject_scheme":"NDC"}]},"item_8_text_21":{"attribute_name":"出版者別名","attribute_value_mlt":[{"subitem_text_value":"Center for International Research on the Japanese Economy"}]},"item_8_text_4":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"University of Tokyo"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"metadata only access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_14cb"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Abe, Makoto"}],"nameIdentifiers":[{"nameIdentifier":"98280","nameIdentifierScheme":"WEKO"}]}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"pate transition","subitem_subject_scheme":"Other"},{"subitem_subject":"prediction model","subitem_subject_scheme":"Other"},{"subitem_subject":"log file","subitem_subject_scheme":"Other"},{"subitem_subject":"statistical modeling","subitem_subject_scheme":"Other"},{"subitem_subject":"Markov transition matrix","subitem_subject_scheme":"Other"},{"subitem_subject":"data mining","subitem_subject_scheme":"Other"}]},"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":"technical report","resourceuri":"http://purl.org/coar/resource_type/c_18gh"}]},"item_title":"A Two-Stage Prediction Model for Web Page Transition","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"A Two-Stage Prediction Model for Web Page Transition"}]},"item_type_id":"8","owner":"1","path":["7436","7434"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-01-17"},"publish_date":"2017-01-17","publish_status":"0","recid":"42731","relation_version_is_last":true,"title":["A Two-Stage Prediction Model for Web Page Transition"],"weko_creator_id":"1","weko_shared_id":null},"updated":"2022-12-19T04:16:41.478852+00:00"}