LEADER 01173nam--2200397---450- 001 990001578920203316 005 20070423135918.0 035 $a000157892 035 $aUSA01000157892 035 $a(ALEPH)000157892USA01 035 $a000157892 100 $a20040419d1978----km-y0itay0103----ba 101 0 $aita 102 $aIT 105 $a||||||||001yy 200 1 $a<> regione$euno spazio per vivere 205 $fedizione italiana a cura di Marica Milanesi 210 $aMilano$cAngeli$d1978 215 $a203 p.$d22 cm 225 2 $aGeografia umana 300 $atrad. di Marica Milanesi 410 0$12001$aGeografia umana 454 1$12001$aLa region, espace vecu$921743 461 1$1001-------$12001 700 1$aFREMONT,$bArmand$0130605 702 1$aMILANESI,$bMarica 801 0$aIT$bsalbc$gISBD 912 $a990001578920203316 951 $aIII.1. Coll. 8/ 24(I C coll. 26/28)$b81457 L.M.$cI C 959 $aBK 969 $aUMA 979 $aSIAV1$b10$c20040419$lUSA01$h1455 979 $aCOPAT4$b90$c20050302$lUSA01$h1318 979 $aCOPAT5$b90$c20070423$lUSA01$h1359 996 $aLa region, espace vecu$921743 997 $aUNISA LEADER 04714nam 22006855 450 001 9910299047903321 005 20200702165523.0 010 $a1-4939-0530-9 024 7 $a10.1007/978-1-4939-0530-0 035 $a(CKB)2550000001280325 035 $a(EBL)1698090 035 $a(OCoLC)881166033 035 $a(SSID)ssj0001199756 035 $a(PQKBManifestationID)11690864 035 $a(PQKBTitleCode)TC0001199756 035 $a(PQKBWorkID)11215137 035 $a(PQKB)10297075 035 $a(MiAaPQ)EBC1698090 035 $a(DE-He213)978-1-4939-0530-0 035 $a(PPN)178317330 035 $a(EXLCZ)992550000001280325 100 $a20140412d2014 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aRecommender Systems for Technology Enhanced Learning $eResearch Trends and Applications /$fedited by Nikos Manouselis, Hendrik Drachsler, Katrien Verbert, Olga C. Santos 205 $a1st ed. 2014. 210 1$aNew York, NY :$cSpringer New York :$cImprint: Springer,$d2014. 215 $a1 online resource (309 p.) 300 $aDescription based upon print version of record. 311 $a1-4939-0529-5 320 $aIncludes bibliographical references. 327 $aCollaborative Filtering Recommendation of Educational Content in Social Environments utilizing Sentiment Analysis Techniques -- Towards automated evaluation of learning resources inside repositories -- Linked Data and the Social Web as facilitators for TEL recommender systems in research and practice -- The Learning Registry: Applying Social Metadata for Learning Resource Recommendations -- A Framework for Personalised Learning-Plan Recommendations in Game-Based Learning -- An approach for an Affective Educational Recommendation Model -- The Case for Preference-Inconsistent Recommendations -- Further Thoughts on Context-Aware Paper Recommendations for Education -- Towards a Social Trust-aware Recommender for Teachers -- ALEF: from Application to Platform for Adaptive Collaborative Learning -- Two Recommending Strategies to enhance Online Presence in Personal Learning Environments -- Recommendations from Heterogeneous Sources in a Technology Enhanced Learning Ecosystem -- COCOON CORE: CO-Author Recommendations based on Betweenness Centrality and Interest Similarity -- Scientific Recommendations to Enhance Scholarly Awareness and Foster Collaboration. 330 $aAs an area, Technology Enhanced Learning (TEL) aims to design, develop and test socio-technical innovations that will support and enhance learning practices of individuals and organizations. Information retrieval is a pivotal activity in TEL and the deployment of recommender systems has attracted increased interest during the past years. Recommendation methods, techniques and systems open an interesting new approach to facilitate and support learning and teaching. The goal is to develop, deploy and evaluate systems that provide learners and teachers with meaningful guidance in order to help identify suitable learning resources from a potentially overwhelming variety of choices. Contributions address the following topics: i) user and item data that can be used to support learning recommendation systems and scenarios, ii) innovative methods and techniques for recommendation purposes in educational settings and iii) examples of educational platforms and tools where recommendations are incorporated. 606 $aArtificial intelligence 606 $aEducation 606 $aComputers 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aEducation, general$3https://scigraph.springernature.com/ontologies/product-market-codes/O00000 606 $aInformation Systems and Communication Service$3https://scigraph.springernature.com/ontologies/product-market-codes/I18008 615 0$aArtificial intelligence. 615 0$aEducation. 615 0$aComputers. 615 14$aArtificial Intelligence. 615 24$aEducation, general. 615 24$aInformation Systems and Communication Service. 676 $a004 676 $a005.7 676 $a006.3 676 $a370 702 $aManouselis$b Nikos$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aDrachsler$b Hendrik$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aVerbert$b Katrien$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSantos$b Olga C$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a9910299047903321 996 $aRecommender Systems for Technology Enhanced Learning$92276659 997 $aUNINA