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Authors

Jarmo Laaksolahti

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Publications by Jarmo Laaksolahti (bibliography)

» 2007 «

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Isbister, Katherine, Höök, Kia, Laaksolahti, Jarmo and Sharp, Michael (2007): The sensual evaluation instrument: Developing a trans-cultural self-report measure of affect. In International Journal of Human-Computer Studies, 65 (4) pp. 315-328

“In this paper we describe the development and testing of a tool for self-assessment of affect while interacting with computer systems, meant to be used in many cultures. We discuss our research approach within the context of existing cultural, affective and HCI theory, and describe testing of its effectiveness in the US and Sweden.”

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» 2006 «

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Isbister, Katherine, Höök, Kristina, Sharp, Michael and Laaksolahti, Jarmo (2006): The sensual evaluation instrument: developing an affective evaluation tool. In: Proceedings of ACM CHI 2006 Conference on Human Factors in Computing Systems 2006. pp. 1163-1172. Available online

“In this paper we describe the development and initial testing of a tool for self-assessment of affect while interacting with computer systems: the Sensual Evaluation Instrument. We discuss our research approach within the context of existing affective and HCI theory, and describe stages of evolution of the tool, and initial testing of its effectiveness.”

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» 2003 «

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Laaksolahti, Jarmo, Bergmark, Niklas and Hedlund, Erik (2003): Enhancing Believability Using Affective Cinematography. In: Rist, Thomas, Aylett, Ruth, Ballin, Daniel and Rickel, Jeff (eds.) IVA 2003 - Intelligent Agents - 4th International Workshop September 15-17, 2003, Kloster Irsee, Germany. pp. 264-268. Available online

» 2001 «

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Svensson, Martin, Höök, Kristina, Laaksolahti, Jarmo and Waern, Annika (2001): Social Navigation of Food Recipes. In: Beaudouin-Lafon, Michel and Jacob, Robert J. K. (eds.) Proceedings of the ACM CHI 2001 Human Factors in Computing Systems Conference March 31 - April 5, 2001, Seattle, Washington, USA. pp. 341-348. Available online

“The term Social Navigation captures every-day behaviour used to find information, people, and places - namely through watching, following, and talking to people. We discuss how to design information spaces to allow for social navigation. We applied our ideas in a recipe recommendation system. In a follow-up user study, subjects state that social navigation adds value to the service: it provides for social affordance, and it helps turning a space into a social place. The study also reveals some unresolved design issues, such as the snowball effect where more and more users follow each other down the wrong path, and privacy issues.”

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» 2000 «

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Svensson, Martin, Laaksolahti, Jarmo, Höök, Kristina and Waern, Annika (2000): A Recipe Based On-Line Food Store. In: Lieberman, Henry (ed.) International Conference on Intelligent User Interfaces 2000 January 9-12, 2000, New Orleans, Louisiana, USA. pp. 260-263. Available online

“Recent research in the area of information retrieval hypothesizes that people benefit from social clues, so called social navigation, when they try to navigate information spaces [7]. We have designed an on-line grocery store building upon those ideas manifested in several different ways. The most central feature is that the system uses a combination of content-based and collaborative filtering as the basis for recipe recommendations. This filtering process can in turn be controlled by editors, whose role is to control the content of the "recipe clubs". Other types of social clues are also present, such as displaying how many users that have chosen a recipe. Finally, the system shows information about other users currently present in the system, and allows users to get in direct contact through chat.”

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Laaksolahti, Jarmo (2000): Explaining Recommendation through User Groups. In: Proceedings of the First Nordic Conference on Human-Computer Interaction 2000. .

“Recommender systems are a specific type of information filtering tools that have emerged in recent years. Until now research in recommender systems has been focused on developing algorithms for collaborative filtering, little effort has gone into considering how users understand recommendations. We describe a system that visualizes the structure of the user population thereby making it easier to understand what recommendations are based on and thus anticipate the effect of your own actions.”

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» 1999 «

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Waern, Annika, Tierney, Mark, Rudsstrom, Asa and Laaksolahti, Jarmo (1999): ConCall: Edited and Adaptive Information Filtering. In: Maybury, Mark T. (ed.) International Conference on Intelligent User Interfaces 1999 January 5-8, 1999, Redondo Beach, California, USA. p. 185. Available online

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