Name
Abstract | ||
|---|---|---|
Personalizing news content requires to choose the appropriate depth of personalization and to assess the extent to which readers' explicit expressions of interest in general and specific news topics can be used as the basis for personalization. A preliminary survey examined 117 respondents' attitudes towards news content personalization and their interest in various news topics and subtopics. The second survey examined 23 participants' declared and actual interests. Participants preferred personalization based on general news topics. Declared interest in general news topics adequately predicted the actual interests in some topics, while in others users' interests differed between general news topics and subtopics. The variance in interest in items also differed among topics. Thus, different personalization methods should be used for different topics. For some, such as 'Sports', users show either high interest or no interest at all. In the latter case most articles related to the topic should be removed, with the exception of items that refer to unique events that may raise general interest according to the expressed interest. In other topics, such as 'Science & Technology', most users are interested in important articles, even if they are not interested in the general news topic. Here, the filtering technique should identify the important articles and present them to all readers. The results can be used to develop effective and simple personalization mechanisms which can be applied to the personalization of news, as well as to other domains. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.ijhcs.2009.09.011 | Int. J. Hum.-Comput. Stud. |
Keywords | Field | DocType |
different personalization method,important article,high interest,user attitude,general news topic,general interest,actual interest,specific news topic,personalizing news content,various news topic,news content personalization | World Wide Web,Expression (mathematics),Computer science,News values,User interface,Personalization | Journal |
Volume | Issue | ISSN |
68 | 8 | International Journal of Human - Computer Studies |
Citations | PageRank | References |
19 | 0.96 | 21 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Talia Lavie | 1 | 434 | 24.59 |
| Michal Sela | 2 | 21 | 1.35 |
| Ilit Oppenheim | 3 | 27 | 2.60 |
| Ohad Inbar | 4 | 74 | 8.88 |
| Joachim Meyer | 5 | 376 | 41.28 |