Supporting exploratory video retrieval tasks with grouping and recommendation

• Published in: Information processing & management Vol. 50; no. 6; pp. 876 - 898
• Main Authors: Halvey, Martin, Vallet, David, Hannah, David, Jose, Joemon M.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01-11-2014; Elsevier; Elsevier Science Ltd
• Subjects: Collaborative; Digital video; Exact sciences and technology; Feedback; Filtering systems; Image retrieval; Implicit; Information and communication sciences; Information processing and retrieval; Information retrieval; Information retrieval systems. Information and document management system; Information retrieval. Man machine relationship; Information science. Documentation; Interface; Perceptions; Research process. Evaluation; Sciences and techniques of general use; Search; Semantics; Studies; User behavior; Video; Implicit; Feedback; Video; Collaborative; Interface; Search; User interface; Feedback regulation; Video recording; Recommendation
• ISSN: 0306-4573; 1873-5371
• DOI: 10.1016/j.ipm.2014.06.004

•Combine grouping of video search results with recommendation techniques to assist video retrieval.•Evaluate grouping and recommendation techniques in separate evaluations to assess impact.•Different recommendation approaches are relevant to the users at different stages of their search.•Organisational and recommendation functionalities can result in a significant improvement on the users’ search performance.
In this paper, we present ViGOR (Video Grouping, Organisation and Recommendation), an exploratory video retrieval system. Exploratory video retrieval tasks are hampered by the lack of semantics associated to video and the overwhelming amount of video items stored in these types of collections (e.g. YouTube, MSN video, etc.). In order to help facilitate these exploratory video search tasks we present a system that utilises two complementary approaches: the first a new search paradigm that allows the semantic grouping of videos and the second the exploitation of past usage history in order to provide video recommendations. We present two types of recommendation techniques adapted to the grouping search paradigm: the first is a global recommendation, which couples the multi-faceted nature of explorative video retrieval tasks with the current user need of information in order to provide recommendations, and second is a local recommendation, which exploits the organisational features of ViGOR in order to provide more localised recommendations based on a specific aspect of the user task. Two user evaluations were carried out in order to (1) validate the new search paradigm provided by ViGOR, characterised by the grouping functionalities and (2) evaluate the usefulness of the proposed recommendation approaches when integrated into ViGOR. The results of our evaluations show (1) that the grouping, organisational and recommendation functionalities can result in an improvement in the users’ search performance without adversely impacting their perceptions of the system and (2) that both recommendation approaches are relevant to the users at different stages of their search, showing the importance of using multi-faceted recommendations for video retrieval systems and also illustrating the many uses of collaborative recommendations for exploratory video search tasks.