dc.contributor.author |
Christidis, K |
en |
dc.contributor.author |
Mentzas, G |
en |
dc.date.accessioned |
2014-03-01T02:52:32Z |
|
dc.date.available |
2014-03-01T02:52:32Z |
|
dc.date.issued |
2010 |
en |
dc.identifier.uri |
https://dspace.lib.ntua.gr/xmlui/handle/123456789/35913 |
|
dc.subject |
Knowledge Modeling |
en |
dc.subject |
Latent Dirichlet Allocation |
en |
dc.subject |
recommender system |
en |
dc.subject |
Social Software |
en |
dc.subject |
Social System |
en |
dc.title |
Using Probabilistic Topic Models in Enterprise Social Software |
en |
heal.type |
conferenceItem |
en |
heal.identifier.primary |
10.1007/978-3-642-12814-1_3 |
en |
heal.identifier.secondary |
http://dx.doi.org/10.1007/978-3-642-12814-1_3 |
en |
heal.publicationDate |
2010 |
en |
heal.abstract |
Enterprise social software (ESS) systems are open and flexible corporate environments which utilize Web 2.0 technologies to stimulate participation through informal interactions and aggregate these interactions into collective structures. A challenge in these systems is to discover, organize and manage the knowledge model of topics found within the enterprise. In this paper we aim to enhance the search and recommendation |
en |
heal.journalName |
Business Information Systems |
en |
dc.identifier.doi |
10.1007/978-3-642-12814-1_3 |
en |