eng URI http://hdl.handle.net/10795/3399 πληροφορική επεξεργασία δεδομένων συλλογή δεδομένων επεξεργασία δεδομένων In this thesis, we address major challenges in searching temporal document collections. In such collections, documents are created and/or edited over time. Examples of temporal document collections are web archives, news archives, blogs, personal emails and enterprise documents. Unfortunately, traditional IR approaches based on termmatching only can give unsatisfactory results when searching temporal document collections. The reason for this is twofold: the contents of documents are strongly time-dependent, i.e., documents are about events happened at particular time periods, and a query representing an information need can be time-dependent as well, i.e., a temporal query. On the other hand, time-only-based methods fall short when it comes to reasoning about events in social media. During the last few years users create chronologically ordered documents about topics that draw their attention in an ever increasing pace. However, with the vast adoption of social media, new types of marketing campaigns have been developed in order to promote content, i.e. brands, products, celebrities, etc. 135 pp. LOMv1.0 creator LOMv1.0educational validator LOMv1.0 Scientific Coordinator LOMv1.0 Project Executing Organisation 2015-10-27 Digital Library of the Operational Programme "Education and Lifelong Learning" abstract types Text Web mining Text mining Time series Classification Time evolution Social networks Trends Burstiness Χρονοσειρές Κατηγοριοποίηση Χρονική εξέλιξη Κοινωνικά δίκτυα Τάσεις Εξόρυξη δεδομένων 3441748 application/pdf http://repository.edulll.gr/edulll/bitstream/10795/3399/2/3399_1.66_%ce%94%ce%94_27_10_15.pdf URI http://hdl.handle.net/10795/3399 LOMv1.0creator 2016-05-25T10:08:12Z LOMv1.0validator 2016-05-25T10:08:12Z LOMv1.0 gre no no Copyright EYD-EPEDBM (Operational Programme "Education and Lifelong Learning")