@book{
 title = {Intelligent Data Engineering and Automated Learning – IDEAL 2014},
 type = {book},
 year = {2014},
 identifiers = {[object Object]},
 volume = {8669},
 websites = {http://link.springer.com/10.1007/978-3-319-10840-7},
 publisher = {Springer International Publishing},
 city = {Cham},
 series = {Lecture Notes in Computer Science},
 editors = {[object Object],[object Object],[object Object],[object Object]},
 id = {d9466fe9-367e-387a-875f-74f9d28e18a0},
 created = {2014-12-13T02:37:04.000Z},
 accessed = {2014-12-13},
 file_attached = {false},
 profile_id = {15d5ede6-80ea-3b4c-a7e1-5b79ba86707d},
 group_id = {a7fbd406-18f3-3b0b-bf98-38c617d1e04e},
 last_modified = {2017-03-14T17:40:34.521Z},
 tags = {ayse,feedback,personalisation,text mining},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {MOOCs offer free access to educational materials, leading to large numbers of students registered in MOOCs courses. The MOOCs forums allow students to post comments and ask questions; due to the number of students, however, the course facilitators are not able to provide feedback in a timely manner. To address this problem, we identify content-knowledge related posts using a course domain ontology and provide students with timely informative automatic feedback. Moreover, we provide facilitators with feedback of students posts, such as frequent topics students ask about. Experimental results from one of the courses offered by Coursera show the potential of our approach in creating a responsive learning environment.},
 bibtype = {book},
 author = {Shatnawi, Safwan and Gaber, Mohamad Medhat and Cocea, Mihaela}
}

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