Access the full text.
Sign up today, get DeepDyve free for 14 days.
TG Kolda (2009)
10.1137/07070111XSIAM Rev, 51
R Koper, B Olivier (2004)
Representing the learning design of units of learningEduc Technol Soc, 7
E García (2009)
10.1007/s11257-008-9047-zUser Model User Adapt Interact, 19
B Schafer, A Konstan, J Riedl (2001)
E-commerce recommendation applicationsData Min Knowl Discov, 5
X Zhou (2012)
10.1007/s10462-011-9222-1Artif Intell Rev, 37
C Cattuto (2007)
10.1073/pnas.0610487104Proc Natl Acad Sci USA, 104
Q Guo (2009)
10.1016/j.knosys.2009.06.001Knowl-Based Syst, 22
J Janssen (2007)
10.1080/10494820701343546Interact Learn Environ, 15
J Hwang, L Hsiao, R Tseng (2003)
A computer-assisted approach to diagnosing student learning problems in science coursesJ Inf Sci Eng, 19
Y Koren (2009)
10.1109/MC.2009.263Computer, 42
D Lemire (2005)
10.1023/B:INRT.0000048492.50961.a6Inf Retr, 8
D Sampson, C Karagiannidis, D Kinshuk (2010)
Personalised learning: educational, technological and standarisation perspectiveDigit Educ Rev, 4
K Verbert (2012)
10.1109/TLT.2012.11IEEE Trans Learn Technol, 5
C Cattuto, V Loreto, L Pietronero (2007)
Semiotic dynamics and collaborative taggingProc Natl Acad Sci USA, 104
L Shen, R Shen (2005)
Ontology-based learning content recommendationInt J Contin Eng Educ Life Long Learn, 15
L Lathauwer De (2000)
10.1137/S0895479896305696SIAM J Matrix Anal Appl, 21
M Winget (2006)
User-defined classification on the online photo sharing site Flickr... or, how I learned to stop worrying and love the million typing monkeysAdv Classif Res Online, 17
M Feng, N Heffernan, K Koedinger (2009)
Addressing the assessment challenge with an online system that tutors as it assessesUser Model User Adapt Interact, 19
C Veres (2006)
Concept modeling by the masses: folksonomy structure and interoperabilityLect Notes Comput Sci, 4215
M Balabanović (1997)
10.1145/245108.245124Commun ACM, 40
KW Cheung (2003)
10.1016/S0167-9236(02)00108-2Decis Support Syst, 35
M Deshpande (2004)
10.1145/963770.963776ACM Trans Inf Syst, 22
JM Chen (2014)
10.1016/j.compedu.2013.09.002Comput Educ, 70
KI Ghauth, NA Abdullah (2010)
Learning materials recommendation using good learners’ ratings and content-based filteringEduc Technol Res Dev, 58
K Cho, CD Schunn, RW Wilson (2006)
Validity and reliability of scaffolded peer assessment of writing from instructor and student perspectivesJ Educ Psychol, 98
MJ Tippins (2003)
10.1002/smj.337Strateg Manag J, 24
L Lathauwer, B Moor, J Vandewalle (2000)
Multilinear singular value decompositionSIAM J Matrix Anal Appl, 21
A Walker, M Recker, K Lawless, D Wiley (2004)
Collaborative information filtering: a review and an educational applicationInt J Artif Intell Educ, 14
S Brin, L Page (1998)
The anatomy of a large-scale hypertextual web search engineComput Netw ISDN Syst, 30
H Drachsler (2008)
10.1504/IJLT.2008.019376Int J Learn Technol, 3
R Agrawal, T Imielinski, A Swami (1993)
Database mining: a performance perspectiveIEEE Trans Knowl Data Eng, 5
JW Keefe (1979)
Student learning styles: diagnosing and prescribing programs
DM Dunlavy, TG Kolda, E Acar (2011)
Temporal link prediction using matrix and tensor factorizationsACM Trans Knowl Discov Data, 5
E García, C Romero, S Ventura, C Castro (2009)
An architecture for making recommendations to courseware authors using association rule mining and collaborative filteringUser Model User Adapt Interact, 19
A Staikopoulos (2014)
10.2298/CSIS121227012SComput Sci Inf Syst, 11
M Deshpande, G Karypis (2004)
Item-based top-n recommendation algorithmsACM Trans Inf Syst, 22
K Verbert, N Manouselis, X Ochoa, M Wolpers, H Drachsler, I Bosnic, E Duval (2012)
Context aware recommender systems for learning: a survey and future challengesIEEE Trans Learn Technol, 5
B Schafer (2001)
10.1023/A:1009804230409Data Min Knowl Discov, 5
E Gaudioso (2009)
10.1016/j.eswa.2007.12.035Expert Syst Appl, 36
M Berry (1994)
10.1137/1037127SIAM Rev, 37
PJ Muñoz-Merino (2015)
10.2298/CSIS140103084MComput Sci Inf Syst, 12
L Gayo, P Ordóñez de Pablos, JM Cueva Lovelle (2010)
Wesonet: applying semantic web technologies and collaborative tagging to multimedia web information systemsComput Hum Behav, 26
B Vesin, M Ivanović, A Klašnja-Milićević, Z Budimac (2013)
Ontology-based architecture with recommendation strategy in java tutoring systemComput Sci Inf Syst, 10
D Wilson, B Smyth, D Sullivan (2003)
Sparsity reduction in collaborative recommendation: a case-based approachInt J Pattern Recognit Artif Intell, 17
DM Dunlavy (2011)
10.1145/1921632.1921636ACM Trans Knowl Discov Data, 5
M Feng (2009)
10.1007/s11257-009-9063-7User Model User Adapt Interact, 19
L Gayo (2010)
10.1016/j.chb.2009.10.004Comput Hum Behav, 26
N Manouselis, C Costopoulou (2007)
Experimental analysis of design choices in a multi-attribute utility collaborative filtering systemInt J Pattern Recognit Artif Intell, 21
M Recker, A Walker (2003)
Supporting ‘word-of-mouth’ social networks via collaborative information filteringJ Interact Learn Res, 14
KI Ghauth (2010)
10.1007/s11423-010-9155-4Educ Technol Res Dev, 58
SM Cox, KC Tsai (2013)
Exploratory examination of relationships between learning styles and learner satisfaction in different course delivery typesInt J Soc Sci Res, 1
B Liu, H Wynne, C Shu, M Yiming (2000)
Analyzing the subjective interestingness of association rulesIEEE Intell Syst, 15
J Janssen, B Berg, C Tattersall, H Hummel, R Koper (2007)
Navigational support in lifelong learning: enhancing effectiveness through indirect social navigationInteract Learn Environ, 15
P Massa, P Avesani (2004)
Trust-aware collaborative filtering for recommender systemsCoopIS/DOA/ODBASE, 1
MJ Tippins, RS Sohi (2003)
IT competency and firm performance: is organizational learning a missing link?Strateg Manag J, 24
A Klašnja-Milićević, B Vesin, M Ivanović, Z Budimac (2011)
e-learning personalization based on hybrid recommendation strategy and learning style identificationComput Educ, 56
C Romero, S Ventura (2006)
Educational data mining: a survey from 1995 to 2005Expert Syst Appl, 33
TG Kolda, BW Bader (2009)
Tensor decompositions and applicationsSIAM Rev, 51
MD Lytras, P Ordóñez de Pablos (2011)
Software technologies in knowledge societyJ Univers Comput Sci, 17
E Gaudioso, M Montero, L Talavera, F Hernandez-del-Olmo (2009)
Supporting teachers in collaborative student modeling: a framework and an implementationExpert Syst Appl, 36
M Balabanović, Y Shoham (1997)
Fab: content-based, collaborative recommendationCommun ACM, 40
P Lops (2013)
10.1007/s10844-012-0215-6J Intell Inf Syst, 40
D Lemire (2005)
Scale and translation invariant collaborative filtering systemsInf Retr, 8
L Bottou (2004)
Advanced lectures on machine learning
C Veres (2006)
The language of folksonomies: what tags reveal about user classificationLect Notes Comput Sci, 3999
KW Cheung, JT Kwok, MH Law, KC Tsui (2003)
Mining customer product ratings for personalized marketingDecis Support Syst, 35
C Veres (2006)
10.1007/11765448_6Lect Notes Comput Sci, 3999
J Srivastava, R Cooley, M Deshpande, P Tan (2000)
Web usage mining: discovery and applications of usage patterns from web dataACM SIGKDD Explor, 1
N Manouselis (2007)
10.1142/S021800140700548XInt J Pattern Recognit Artif Intell, 21
A Palmatier, M Bennet (1974)
Note-taking habits of college studentsJ Read, 18
JL Herlocker (2004)
10.1145/963770.963772ACM Trans Inf Syst, 22
RE DeRouin, BA Fritzsche, E Salas (2004)
Optimizing e-learning: research-based guidelines for learnercontrolled trainingHum Resour Manag, 43
H Drachsler, HGK Hummel, R Koper (2008)
Personal recommender systems for learners in lifelong learning networks: the requirements, techniques and modelInt J Learn Technol, 3
SM Cox (2013)
10.5296/ijssr.v1i1.4100Int J Soc Sci Res, 1
TY Tang, G McCalla (2005)
Smart recommendation for an evolving e-learning system: architecture and experimentInt J e-Learn, 4
G Šimić (2004)
10.2298/CSIS0401141SComSIS, 1
PJ Muñoz-Merino, CD Kloos, M Muñoz-Organero, A Pardo (2015)
A software engineering model for the development of adaptation rules and its application in a hinting adaptive E-learning systemComput Sci Inf Syst, 12
G Šimić (2004)
The multi-courses tutoring system designComSIS, 1
Y Koren, R Bell, C Volinsky (2009)
Matrix factorization techniques for recommender systemsComputer, 42
S Brin (1998)
10.1016/S0169-7552(98)00110-XComput Netw ISDN Syst, 30
D Pierrakos, G Paliouras, C Papatheodorou, C Spyropoulos (2003)
Web usage mining as a tool for personalization: a surveyUser Model User Adapt Interact, 13
K Cho (2007)
10.1016/j.compedu.2005.02.004Comput Educ, 48
M Recker, A Walker, K Lawless (2003)
What do you recommend? Implementation and analyses of collaborative filtering of web resources for educationInstr Sci, 31
JL Herlocker, JA Konstan, LG Terveen, J Riedl (2004)
Evaluating collaborative filtering recommender systemsACM Trans Inf Syst, 22
A Klašnja-Milićević (2011)
10.1016/j.compedu.2010.11.001Comput Educ, 56
I Doush (2011)
Annotations, collaborative tagging, and searching mathematics in E-learning IJACSAInt J Adv Comput Sci Appl, 2
G Adomavicius, A Tuzhilin (2005)
Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensionsIEEE Trans Knowl Data Eng, 17
T Landauer, P Foltz, D Laham (1998)
Introduction to latent semantic analysisDiscourse Process, 25
S Rendle (2011)
Context-aware ranking with factorization models
X Zhou, Y Xu, Y Li, A Josang, C Cox (2012)
The state-of-the-art in personalized recommender systems for social networkingArtif Intell Rev, 37
P Resnick (1997)
10.1145/245108.245121Commun ACM, 40
D Pierrakos (2003)
10.1023/A:1026238916441User Model User Adapt Interact, 13
Q Guo, M Zhang (2009)
Implement web learning environment based on data miningKnowl-Based Syst, 22
JM Chen, MC Chen, YS Sun (2014)
A tag based learning approach to knowledge acquisition for constructing prior knowledge and enhancing student-reading comprehensionComput Educ, 70
M Recker (2003)
10.1023/A:1024686010318Instr Sci, 31
R Agrawal (1993)
10.1109/69.250074IEEE Trans Knowl Data Eng, 5
D Lemire (2005)
10.1108/17415650580000043Int J Interact Technol Smart Educ, 2
S Rendle (2011)
10.1007/978-3-642-16898-7
K Cho, CD Schunn (2007)
Scaffolded writing and rewriting in the discipline: a web-based reciprocal peer review systemComput Educ, 48
T Landauer (1998)
10.1080/01638539809545028Discourse Process, 25
B Vesin (2013)
10.2298/CSIS111231001VComput Sci Inf Syst, 10
D Wilson (2003)
10.1142/S0218001403002678Int J Pattern Recognit Artif Intell, 17
C Ciro, C Schmitz, A Baldassarri, V Servedio, V Loreto, A Hotho (2007)
Network properties of folksonomiesAI Commun, 20
C Deerwester, T Dumais, K Landauer, W Furnas, A Harshman (1990)
Indexing by latent semantic analysisJ ASIS, 41
D Lemire, H Boley, S McGrath, M Ball (2005)
Collaborative filtering and inference rules for context-aware learning object recommendationInt J Interact Technol Smart Educ, 2
P Resnick, H Varian (1997)
Recommender systemsCommun ACM, 40
K Cho (2006)
10.1037/0022-0663.98.4.891J Educ Psychol, 98
G Adomavicius (2005)
10.1109/TKDE.2005.99IEEE Trans Knowl Data Eng, 17
M Winget (2006)
10.7152/acro.v17i1.12496Adv Classif Res Online, 17
J Bar-Ilan (2008)
10.1108/14684520810914016Online Inf Rev, 32
C Romero (2006)
10.1016/j.eswa.2006.04.005Expert Syst Appl, 33
A Staikopoulos, I O’Keeffe, R Rafter, E Walsh, B Yousuf, O Conlan, V Wade (2014)
AMASE: a framework for supporting personalised activity-based learning on the webComput Sci Inf Syst, 11
RVVSV Prasad, VV Kumari (2012)
A categorical review of recommender systemsSystem, 1
RE DeRouin (2004)
10.1002/hrm.20012Hum Resour Manag, 43
J Srivastava (2000)
10.1145/846183.846188ACM SIGKDD Explor, 1
L Shen (2005)
10.1504/IJCEELL.2005.007719Int J Contin Eng Educ Life Long Learn, 15
C Romero, S Ventura, PD Bra (2004)
Knowledge discovery with genetic programming for providing feedback to courseware authorUser Model User Adapt Interact, 14
P Lops, M Gemmis, G Semeraro, C Musto, F Narducci (2013)
Content-based and collaborative techniques for tag recommendation: an empirical evaluationJ Intell Inf Syst, 40
W Chen, B Wasson (2002)
Coordinating collaborative knowledge buildingProc Int Conf Appl Inform, 25
B Liu (2000)
10.1109/5254.889106IEEE Intell Syst, 15
M Berry, S Dumais, G O’Brien (1994)
Using linear algebra for intelligent information retrievalSIAM Rev, 37
C Romero (2004)
10.1007/s11257-004-7961-2User Model User Adapt Interact, 14
J Bar-Ilan, S Shoham, A Idan, Y Miller, A Shachak (2008)
Structured versus unstructured tagging: a case studyOnline Inf Rev, 32
A Merceron, K Yacef (2004)
Mining student data captured from a web-based tutoring toolJ Interact Learn Res, 15
A Silberschatz, A Tuzhilin (1996)
What makes pattterns interesting in knowledge discovery systemsIEEE Trans Knowl Data Eng, 8
A Silberschatz (1996)
10.1109/69.553165IEEE Trans Knowl Data Eng, 8
C Veres (2006)
10.1007/11901181_25Lect Notes Comput Sci, 4215
L Bottou (2004)
10.1007/978-3-540-28650-9_7
With the development of sophisticated e-learning environments, personalization is becoming an important feature in e-learning systems due to the differences in background, goals, capabilities and personalities of the large numbers of learners. Personalization can achieve using different type of recommendation techniques. This paper presents an overview of the most important requirements and challenges for designing a recommender system in e-learning environments. The aim of this paper is to present the various limitations of the current generation of recommendation techniques and possible extensions with model for tagging activities and tag-based recommender systems, which can apply to e-learning environments in order to provide better recommendation capabilities.
Artificial Intelligence Review – Springer Journals
Published: Sep 30, 2015
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.