User interests mining based on Topic Map
In this paper, we propose a method for mining user interests based on topic map in an e-learning system. It is now widely assumed that in personalized information area user interests plays an important role in document recommendation. User interests generally reflect the user background and topics o...
Gespeichert in:
Hauptverfasser: | , |
---|---|
Format: | Tagungsbericht |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 2402 |
---|---|
container_issue | |
container_start_page | 2399 |
container_title | |
container_volume | 5 |
creator | Wei Kuang Nianlong Luo |
description | In this paper, we propose a method for mining user interests based on topic map in an e-learning system. It is now widely assumed that in personalized information area user interests plays an important role in document recommendation. User interests generally reflect the user background and topics of interests. Topic Maps is an ISO standard for the representation and interchange of knowledge, which builds a structured semantic web on the layer of information resources. In an e-learning system, topic maps can provide a good semantic model for the course document. Besides with the help of the topic maps, we can build an exact model for user interests. Because in an e-learning system, we can get the users' log and users' learning condition from the server. Thus the system adopts interest mining technology and can automatically identify the learner's interests and recommend interest-related resources. In this paper, we only focus on interests mining and interests modeling. The interest modeling system using new approach based on topic map is more effective. |
doi_str_mv | 10.1109/FSKD.2010.5569519 |
format | Conference Proceeding |
fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_5569519</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5569519</ieee_id><sourcerecordid>5569519</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-c84f97415eb28a8ff34246749341aa536d0772196ada89f4d0264553d4de24363</originalsourceid><addsrcrecordid>eNpFj8FKAzEURSMiqLUfIG6ydDNtXt57mWQp1aq04sJxXdImkYidDpPZ-PcOtODdXM7mXK4Qt6BmAMrNlx-rx5lWIzIbx-DOxDWQJmKHaM__AeBSTEv5VmOItUK-EvefJfYyt0PsYxmK3Oc2t19y60sM8tDK5tDlnXzz3Y24SP6nxOmpJ6JZPjWLl2r9_vy6eFhX2amh2llKribguNXW25Rw3DY1OSTwntEEVdcanPHBW5coKG2IGQOFqAkNTsTdUZtjjJuuz3vf_25Ox_APjno_AA</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>User interests mining based on Topic Map</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Wei Kuang ; Nianlong Luo</creator><creatorcontrib>Wei Kuang ; Nianlong Luo</creatorcontrib><description>In this paper, we propose a method for mining user interests based on topic map in an e-learning system. It is now widely assumed that in personalized information area user interests plays an important role in document recommendation. User interests generally reflect the user background and topics of interests. Topic Maps is an ISO standard for the representation and interchange of knowledge, which builds a structured semantic web on the layer of information resources. In an e-learning system, topic maps can provide a good semantic model for the course document. Besides with the help of the topic maps, we can build an exact model for user interests. Because in an e-learning system, we can get the users' log and users' learning condition from the server. Thus the system adopts interest mining technology and can automatically identify the learner's interests and recommend interest-related resources. In this paper, we only focus on interests mining and interests modeling. The interest modeling system using new approach based on topic map is more effective.</description><identifier>ISBN: 1424459311</identifier><identifier>ISBN: 9781424459315</identifier><identifier>EISBN: 1424459338</identifier><identifier>EISBN: 9781424459339</identifier><identifier>EISBN: 1424459346</identifier><identifier>EISBN: 9781424459346</identifier><identifier>DOI: 10.1109/FSKD.2010.5569519</identifier><language>eng</language><publisher>IEEE</publisher><subject>Adaptation model ; Analytical models ; Computational modeling ; Data mining ; Data models ; interest model ; interests mining ; Solid modeling ; Support vector machine classification ; topic map</subject><ispartof>2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery, 2010, Vol.5, p.2399-2402</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5569519$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5569519$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Wei Kuang</creatorcontrib><creatorcontrib>Nianlong Luo</creatorcontrib><title>User interests mining based on Topic Map</title><title>2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery</title><addtitle>FSKD</addtitle><description>In this paper, we propose a method for mining user interests based on topic map in an e-learning system. It is now widely assumed that in personalized information area user interests plays an important role in document recommendation. User interests generally reflect the user background and topics of interests. Topic Maps is an ISO standard for the representation and interchange of knowledge, which builds a structured semantic web on the layer of information resources. In an e-learning system, topic maps can provide a good semantic model for the course document. Besides with the help of the topic maps, we can build an exact model for user interests. Because in an e-learning system, we can get the users' log and users' learning condition from the server. Thus the system adopts interest mining technology and can automatically identify the learner's interests and recommend interest-related resources. In this paper, we only focus on interests mining and interests modeling. The interest modeling system using new approach based on topic map is more effective.</description><subject>Adaptation model</subject><subject>Analytical models</subject><subject>Computational modeling</subject><subject>Data mining</subject><subject>Data models</subject><subject>interest model</subject><subject>interests mining</subject><subject>Solid modeling</subject><subject>Support vector machine classification</subject><subject>topic map</subject><isbn>1424459311</isbn><isbn>9781424459315</isbn><isbn>1424459338</isbn><isbn>9781424459339</isbn><isbn>1424459346</isbn><isbn>9781424459346</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpFj8FKAzEURSMiqLUfIG6ydDNtXt57mWQp1aq04sJxXdImkYidDpPZ-PcOtODdXM7mXK4Qt6BmAMrNlx-rx5lWIzIbx-DOxDWQJmKHaM__AeBSTEv5VmOItUK-EvefJfYyt0PsYxmK3Oc2t19y60sM8tDK5tDlnXzz3Y24SP6nxOmpJ6JZPjWLl2r9_vy6eFhX2amh2llKribguNXW25Rw3DY1OSTwntEEVdcanPHBW5coKG2IGQOFqAkNTsTdUZtjjJuuz3vf_25Ox_APjno_AA</recordid><startdate>201008</startdate><enddate>201008</enddate><creator>Wei Kuang</creator><creator>Nianlong Luo</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201008</creationdate><title>User interests mining based on Topic Map</title><author>Wei Kuang ; Nianlong Luo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-c84f97415eb28a8ff34246749341aa536d0772196ada89f4d0264553d4de24363</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Adaptation model</topic><topic>Analytical models</topic><topic>Computational modeling</topic><topic>Data mining</topic><topic>Data models</topic><topic>interest model</topic><topic>interests mining</topic><topic>Solid modeling</topic><topic>Support vector machine classification</topic><topic>topic map</topic><toplevel>online_resources</toplevel><creatorcontrib>Wei Kuang</creatorcontrib><creatorcontrib>Nianlong Luo</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Wei Kuang</au><au>Nianlong Luo</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>User interests mining based on Topic Map</atitle><btitle>2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery</btitle><stitle>FSKD</stitle><date>2010-08</date><risdate>2010</risdate><volume>5</volume><spage>2399</spage><epage>2402</epage><pages>2399-2402</pages><isbn>1424459311</isbn><isbn>9781424459315</isbn><eisbn>1424459338</eisbn><eisbn>9781424459339</eisbn><eisbn>1424459346</eisbn><eisbn>9781424459346</eisbn><abstract>In this paper, we propose a method for mining user interests based on topic map in an e-learning system. It is now widely assumed that in personalized information area user interests plays an important role in document recommendation. User interests generally reflect the user background and topics of interests. Topic Maps is an ISO standard for the representation and interchange of knowledge, which builds a structured semantic web on the layer of information resources. In an e-learning system, topic maps can provide a good semantic model for the course document. Besides with the help of the topic maps, we can build an exact model for user interests. Because in an e-learning system, we can get the users' log and users' learning condition from the server. Thus the system adopts interest mining technology and can automatically identify the learner's interests and recommend interest-related resources. In this paper, we only focus on interests mining and interests modeling. The interest modeling system using new approach based on topic map is more effective.</abstract><pub>IEEE</pub><doi>10.1109/FSKD.2010.5569519</doi><tpages>4</tpages></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISBN: 1424459311 |
ispartof | 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery, 2010, Vol.5, p.2399-2402 |
issn | |
language | eng |
recordid | cdi_ieee_primary_5569519 |
source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Adaptation model Analytical models Computational modeling Data mining Data models interest model interests mining Solid modeling Support vector machine classification topic map |
title | User interests mining based on Topic Map |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-16T05%3A11%3A13IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=User%20interests%20mining%20based%20on%20Topic%20Map&rft.btitle=2010%20Seventh%20International%20Conference%20on%20Fuzzy%20Systems%20and%20Knowledge%20Discovery&rft.au=Wei%20Kuang&rft.date=2010-08&rft.volume=5&rft.spage=2399&rft.epage=2402&rft.pages=2399-2402&rft.isbn=1424459311&rft.isbn_list=9781424459315&rft_id=info:doi/10.1109/FSKD.2010.5569519&rft_dat=%3Cieee_6IE%3E5569519%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=1424459338&rft.eisbn_list=9781424459339&rft.eisbn_list=1424459346&rft.eisbn_list=9781424459346&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5569519&rfr_iscdi=true |