{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T18:35:53Z","timestamp":1764873353462,"version":"3.41.0"},"reference-count":43,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2015,3,11]],"date-time":"2015-03-11T00:00:00Z","timestamp":1426032000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Intell. Syst. Technol."],"published-print":{"date-parts":[[2015,3,11]]},"abstract":"<jats:p>The objective of any tutoring system is to provide resources to learners that are adapted to their current state of knowledge. With the availability of a large variety of online content and the disjunctive nature of results provided by traditional search engines, it becomes crucial to provide learners with adapted learning paths that propose a sequence of resources that match their learning objectives. In an ideal case, the sequence of documents provided to the learner should be such that each new document relies on concepts that have been already defined in previous documents. Thus, the problem of determining an effective learning path from a corpus of web documents depends on the accurate identification of outcome and prerequisite concepts in these documents and on their ordering according to this information. Until now, only a few works have been proposed to distinguish between prerequisite and outcome concepts, and to the best of our knowledge, no method has been introduced so far to benefit from this information to produce a meaningful learning path. To this aim, this article first describes a concept annotation method that relies on machine-learning techniques to predict the class of each concept\u2014prerequisite or outcome\u2014on the basis of contextual and local features. Then, this categorization is exploited to produce an automatic resource sequencing on the basis of different representations and scoring functions that transcribe the precedence relation between learning resources. Experiments conducted on a real dataset built from online resources show that our concept annotation approach outperforms the baseline method and that the learning paths automatically generated are consistent with the ground truth provided by the author of the online content.<\/jats:p>","DOI":"10.1145\/2505349","type":"journal-article","created":{"date-parts":[[2015,3,12]],"date-time":"2015-03-12T12:18:05Z","timestamp":1426162685000},"page":"1-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":15,"title":["Resources Sequencing Using Automatic Prerequisite--Outcome Annotation"],"prefix":"10.1145","volume":"6","author":[{"given":"Sahar","family":"Changuel","sequence":"first","affiliation":[{"name":"Universit\u00e9 Pierre et Marie Curie, Paris, France"}]},{"given":"Nicolas","family":"Labroche","sequence":"additional","affiliation":[{"name":"Universit\u00e9 Pierre et Marie Curie, Paris, France"}]},{"given":"Bernadette","family":"Bouchon-Meunier","sequence":"additional","affiliation":[{"name":"Universit\u00e9 Pierre et Marie Curie, Paris, France"}]}],"member":"320","published-online":{"date-parts":[[2015,3,11]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"D. P. Ausubel. 1963. The Psychology of Meaningful Verbal Learning. Grune & Stratton.  D. P. Ausubel. 1963. The Psychology of Meaningful Verbal Learning. Grune & Stratton."},{"volume-title":"Handbook on Ontologies","author":"Brase Jan","key":"e_1_2_1_2_1","unstructured":"Jan Brase and Wolfgang Nejdl . 2004. Ontologies and metadata for eLearning . In Handbook on Ontologies , Steffen Staab and Rudi Studer (Eds.). Springer , 555--574. Jan Brase and Wolfgang Nejdl. 2004. Ontologies and metadata for eLearning. In Handbook on Ontologies, Steffen Staab and Rudi Studer (Eds.). Springer, 555--574."},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.3115\/974499.974526"},{"key":"e_1_2_1_5_1","volume-title":"WebNet World Conference on the WWW and Internet. AACE, 69--74","author":"Brusilovsky Peter","year":"2000","unstructured":"Peter Brusilovsky . 2000 . Concept-based courseware engineering for large scale web-based education . In WebNet World Conference on the WWW and Internet. AACE, 69--74 . Peter Brusilovsky. 2000. Concept-based courseware engineering for large scale web-based education. In WebNet World Conference on the WWW and Internet. AACE, 69--74."},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1011143116306"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.5555\/648028.745013"},{"key":"e_1_2_1_8_1","volume-title":"Proceedings of the 2004 World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. AACE, 2556--2561","author":"Brusilovsky Peter","year":"2004","unstructured":"Peter Brusilovsky , Michael Yudelson , and Sergey Sosnovsky . 2004 . An adaptive e-learning service for accessing interactive examples . In Proceedings of the 2004 World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. AACE, 2556--2561 . Peter Brusilovsky, Michael Yudelson, and Sergey Sosnovsky. 2004. An adaptive e-learning service for accessing interactive examples. In Proceedings of the 2004 World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. AACE, 2556--2561."},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/1102351.1102363"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/1148170.1148205"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/CIDM.2011.5949296"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/CIDM.2011.5949296"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2010.5596971"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2010.5596971"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/11428817_21"},{"key":"e_1_2_1_16_1","volume-title":"Proceedings of the IJCAI-2001 Workshop on Adaptive Text Extraction and Mining.","author":"Ciravegna Fabio","year":"2001","unstructured":"Fabio Ciravegna . 2001 . (LP)2, an adaptive algorithm for information extraction from web-related texts . In Proceedings of the IJCAI-2001 Workshop on Adaptive Text Extraction and Mining. Fabio Ciravegna. 2001. (LP)2, an adaptive algorithm for information extraction from web-related texts. In Proceedings of the IJCAI-2001 Workshop on Adaptive Text Extraction and Mining."},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1967.1053964"},{"key":"e_1_2_1_18_1","unstructured":"W. Bruce Croft Donald Metzler and Trevor Strohman. 2009. Search Engines - Information Retrieval in Practice. Pearson Education.   W. Bruce Croft Donald Metzler and Trevor Strohman. 2009. Search Engines - Information Retrieval in Practice. Pearson Education."},{"key":"e_1_2_1_19_1","first-page":"97","article-title":"Automatic extraction of pedagogic metadata from learning content","volume":"18","author":"Devshri Roy","year":"2008","unstructured":"Roy Devshri , Sarkar Sudeshna , and Ghose Sujoy . 2008 . Automatic extraction of pedagogic metadata from learning content . International Journal on Artificial Intelligence Edition 18 , 2 (2008), 97 -- 118 . Roy Devshri, Sarkar Sudeshna, and Ghose Sujoy. 2008. Automatic extraction of pedagogic metadata from learning content. International Journal on Artificial Intelligence Edition 18, 2 (2008), 97--118.","journal-title":"International Journal on Artificial Intelligence Edition"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/1341531.1341542"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1137\/S0895480102412856"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/1013367.1013394"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/376697.376700"},{"volume-title":"Fuzzy Preference Modelling and Multicriteria Decision Support","author":"Fodor J\u00e0nos","key":"e_1_2_1_24_1","unstructured":"J\u00e0nos Fodor and Marc Roubens . 1994. Fuzzy Preference Modelling and Multicriteria Decision Support . Kluwer Academic Publishers . J\u00e0nos Fodor and Marc Roubens. 1994. Fuzzy Preference Modelling and Multicriteria Decision Support. Kluwer Academic Publishers."},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/1076034.1076085"},{"key":"e_1_2_1_26_1","article-title":"Multiple kernel learning algorithms","author":"G\u00f6nen Mehmet","year":"2011","unstructured":"Mehmet G\u00f6nen and Ethem Alpaydin . 2011 . Multiple kernel learning algorithms . Journal of Machine Learning Research 12 ( July 2011), 2211--2268. Mehmet G\u00f6nen and Ethem Alpaydin. 2011. Multiple kernel learning algorithms. Journal of Machine Learning Research 12 (July 2011), 2211--2268.","journal-title":"Journal of Machine Learning Research 12"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1080\/13614560410001728128"},{"volume-title":"Large Margin Rank Boundaries for Ordinal Regression","author":"Herbrich Ralf","key":"e_1_2_1_28_1","unstructured":"Ralf Herbrich , Thore Graepel , and Klaus Obermayer . 2000. Large Margin Rank Boundaries for Ordinal Regression . MIT Press . Ralf Herbrich, Thore Graepel, and Klaus Obermayer. 2000. Large Margin Rank Boundaries for Ordinal Regression. MIT Press."},{"key":"e_1_2_1_29_1","volume-title":"Witten","author":"Franck Eibe","year":"2005","unstructured":"Eibe Franck and Ian H . Witten 2005 . Data Mining : Practical Machine Learning Tools and Techniques (2nd ed.). Diane Cerra . Eibe Franck and Ian H. Witten 2005. Data Mining: Practical Machine Learning Tools and Techniques (2nd ed.). Diane Cerra."},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.5555\/645326.649721"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/775047.775067"},{"key":"e_1_2_1_32_1","first-page":"128","article-title":"Adaptive learning resources sequencing in educational hypermedia systems","volume":"8","author":"Karampiperis Pythagoras","year":"2005","unstructured":"Pythagoras Karampiperis and Demetrios Sampson . 2005 . Adaptive learning resources sequencing in educational hypermedia systems . Educational Technology & Society 8 , 4 (2005), 128 -- 147 . Pythagoras Karampiperis and Demetrios Sampson. 2005. Adaptive learning resources sequencing in educational hypermedia systems. Educational Technology & Society 8, 4 (2005), 128--147.","journal-title":"Educational Technology & Society"},{"volume-title":"Proceedings of the Atlantic Web Intelligence Conference (AWIC\u201907)","author":"Javed","key":"e_1_2_1_33_1","unstructured":"Javed I. Khan and Manas Hardas. 2007. A technique for representing course knowledge using ontologies and assessing test problems . In Proceedings of the Atlantic Web Intelligence Conference (AWIC\u201907) . 174--179. Javed I. Khan and Manas Hardas. 2007. A technique for representing course knowledge using ontologies and assessing test problems. In Proceedings of the Atlantic Web Intelligence Conference (AWIC\u201907). 174--179."},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.3115\/1075096.1075150"},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.5555\/1005332.1005345"},{"key":"e_1_2_1_36_1","volume-title":"Proceedings of the IEEE International Conference on Data Mining. IEEE Computer Society, 369--376","author":"Li Wenmin","year":"2001","unstructured":"Wenmin Li , Jiawei Han , and Jian Pei . 2001 . CMAR: Accurate and efficient classification based on multiple class-association rules . In Proceedings of the IEEE International Conference on Data Mining. IEEE Computer Society, 369--376 . Wenmin Li, Jiawei Han, and Jian Pei. 2001. CMAR: Accurate and efficient classification based on multiple class-association rules. In Proceedings of the IEEE International Conference on Data Mining. IEEE Computer Society, 369--376."},{"key":"e_1_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1108\/eb046814"},{"key":"e_1_2_1_38_1","volume-title":"Programs for Machine Learning","author":"Quinlan Ross","unstructured":"Ross Quinlan . 1993. C4.5 : Programs for Machine Learning ( 1 st ed.). Morgan Kaufmann . Ross Quinlan. 1993. C4.5: Programs for Machine Learning (1st ed.). Morgan Kaufmann.","edition":"1"},{"key":"e_1_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.5555\/1454082.1454084"},{"key":"e_1_2_1_40_1","volume-title":"Stern and Beverly Park Woolf","author":"Mia","year":"1998","unstructured":"Mia K. Stern and Beverly Park Woolf . 1998 . Curriculum sequencing in a web-based tutor. In Intelligent Tutoring Systems, Barry P. Goettl, Henry M. Halff, Carol L. Redfield, and Valerie J. Shute (Eds.). Lecture Notes in Computer Science, Vol. 1452 . Springer , Berlin, 574--583. DOI: http:\/\/dx.doi.org\/10.1007\/3-540-68716-5_63 10.1007\/3-540-68716-5_63 Mia K. Stern and Beverly Park Woolf. 1998. Curriculum sequencing in a web-based tutor. In Intelligent Tutoring Systems, Barry P. Goettl, Henry M. Halff, Carol L. Redfield, and Valerie J. Shute (Eds.). Lecture Notes in Computer Science, Vol. 1452. Springer, Berlin, 574--583. DOI: http:\/\/dx.doi.org\/10.1007\/3-540-68716-5_63"},{"key":"e_1_2_1_41_1","volume-title":"The Nature of Statistical Learning Theory","author":"Vapnik Vladimir N.","unstructured":"Vladimir N. Vapnik . 1999. The Nature of Statistical Learning Theory ( 2 nd ed.). Springer . Vladimir N. Vapnik. 1999. The Nature of Statistical Learning Theory (2nd ed.). Springer.","edition":"2"},{"key":"e_1_2_1_42_1","volume-title":"Proceedings of the International Conference on Computers in Education (ICCE\u201995)","author":"Vassileva Julita","year":"1995","unstructured":"Julita Vassileva . 1995 . Dynamic courseware generation: At the cross point of CAL, ITS and authoring . In Proceedings of the International Conference on Computers in Education (ICCE\u201995) . 290--297. Julita Vassileva. 1995. Dynamic courseware generation: At the cross point of CAL, ITS and authoring. In Proceedings of the International Conference on Computers in Education (ICCE\u201995). 290--297."},{"key":"e_1_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/1277741.1277790"}],"container-title":["ACM Transactions on Intelligent Systems and Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2505349","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2505349","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T07:28:57Z","timestamp":1750231737000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2505349"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,3,11]]},"references-count":43,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2015,3,11]]}},"alternative-id":["10.1145\/2505349"],"URL":"https:\/\/doi.org\/10.1145\/2505349","relation":{},"ISSN":["2157-6904","2157-6912"],"issn-type":[{"type":"print","value":"2157-6904"},{"type":"electronic","value":"2157-6912"}],"subject":[],"published":{"date-parts":[[2015,3,11]]},"assertion":[{"value":"2012-07-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2013-06-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2015-03-11","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}