Category Archives: News

Paper: Creative retrieval practices of media professionals at IAMCR 2016

The first stage of the project is well underway, and so are the first insights! Sabrina Sauer will present insights about the creative retrieval practices of media professionals at the International Association for Media and Communication Research conference in Leicester this July.

Abstract:

Media professionals such as news editors, image researchers, and documentary filmmakers increasingly rely on online access to digital content within audiovisual archives to create stories (Huurnink, Hollink, and De Rijke). Seeking and finding audiovisual sources therefore requires an in-depth knowledge of how to find sources digitally. This paper presents qualitative research insights into how media professionals search and use digital archives to create (trans)medial narratives. In these storytelling practices, production cultures, search technologies and user ideas intertwine. The paper proposes to unravel the dynamics of story production, using the notion of creative retrieval. The term combines ideas from media studies about the effects of media convergence on media content (Erdal, “Researching Media Convergence and Crossmedia News Production – Mapping the Field”), theories about serendipitous information retrieval (Toms), and anthropological studies of creativity (Hallam and Ingold). The paper furthermore exemplifies an ongoing research project in which, to support creative retrieval by media professionals, a user-centered design approach guides the development of new search technologies: open source self-learning search algorithms.

This paper specifically highlights the role of user-technology interactions within the media production process. Research outcomes are theoretically and methodologically based on the recognition that a focus on media users is key to understand how media technologies gain shape and meaning. This view, developed by Science and Technology Studies (Oudshoorn and Pinch; Silverstone and Haddon), also forms the basis of the research’s qualitative user-centered design approach; media professionals are involved in co-design workshops and semi-structured interviews to better understand their search culture and to iteratively build new search algorithms that accommodate audiovisual storytelling needs.

Website: http://iamcr.org/leicester2016

Serendipity and search workshop at CHIIR 2016

Sabrina Sauer presented research insights into how media professionals use audiovisual archives to create audiovisual narratives during the CHIIR 2016 (Chapel Hill, North-Carolina, 13-17 March) workshop “The Serendipity Factor: Evaluation the Affordances of Digital Environments”. The goal of the workshop was to bring together ideas and methods used to understand and facilitate serendipitous search within digital environments. For media professionals, part of creative storytelling depends on serendipitous findings within archives. For more information about the workshop and this topic, please view the workshop’s website

Tutorial on click models for web search at AINL-ISMW FRUCT 2015

Ilya Markov was invited to give a tutorial on user behavior in web search at the AINL-ISMW FRUCT 2015 conference for young scientists, held in St. Petersburg, Russia, on November 9-14. The tutorial discussed how user clicks in web search can be analyzed, interpreted and modeled and how the resulting click models help to improve web search. The information and materials on click models can be found at the dedicated web site.

Paper at DIR 2015

“Learning to Explain Entity Relationships in Knowledge Graphs”, an ACL 2015 paper authored by Nikos Voskarides, Edgar Meij, Manos Tsagkias, Maarten de Rijke and Wouter Weerkamp, will be presented at the Dutch-Belgian Information Retrieval (DIR) workshop on November 27th 2015.

Abstract:
We study the problem of explaining relationships between pairs of knowledge graph entities with human-readable descriptions. Our method extracts and enriches sentences that refer to an entity pair from a corpus and ranks the sentences according to how well they describe the relationship between the entities. We model this task as a learning to rank problem for sentences and employ a rich set of features. When evaluated on a large set of manually annotated sentences, we find that our method significantly improves over state-of-the-art baseline models.

The project has kicked-off!

The MediaNow project has officially kicked-off. Today, the team and partners met up to discuss the project’s plans and shared ideas about MediaNow. Because how do media-professionals, retrieval specialists, R&D professionals and technical experts see the future of creative retrieval, and self-learning search algorithms?

After a round of introductions and presentations by the research team, the group got to work and collectively discussed the current needs of media-professionals when it comes to audio-visual retrieval. Ideas for immediate feature requests surfaced as did more meta and multi-perspectival “the sky is the limit” conceptualizations of what an ideal retrieval experience would look like. And questions surfaced: is it possible to build an algorithm that makes creative associations and storylines between entities?

The morning ended with short presentations by the partners about who they felt “the media-professional” is, and what current and future needs and characteristics of this professional are. The kick-off has provided a lot of food for thought for the team!

 

We’ll be hiring soon

We’ll soon be advertising for candidates to form a research team with a four-year PhD student and a three-year postdoc in information retrieval and a three-year postdoc in media studies. The advertisements will be broadcast soon.