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Ruthven, I.; Lalmas, M.: Selective relevance feedback using term characteristics (1999)
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- Source
- Vocabulary as a central concept in digital libraries: interdisciplinary concepts, challenges, and opportunities : proceedings of the Third International Conference an Conceptions of Library and Information Science (COLIS3), Dubrovnik, Croatia, 23-26 May 1999. Ed. by T. Arpanac et al
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Blanke, T.; Lalmas, M.; Huibers, T.: ¬A framework for the theoretical evaluation of XML retrieval (2012)
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Lalmas, M.; Ruthven, I.: ¬A model for structured document retrieval : empirical investigations (1997)
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Ruthven, T.; Lalmas, M.; Rijsbergen, K.van: Incorporating user research behavior into relevance feedback (2003)
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- Abstract
- Ruthven, Mounia, and van Rijsbergen rank and select terms for query expansion using information gathered on searcher evaluation behavior. Using the TREC Financial Times and Los Angeles Times collections and search topics from TREC-6 placed in simulated work situations, six student subjects each preformed three searches on an experimental system and three on a control system with instructions to search by natural language expression in any way they found comfortable. Searching was analyzed for behavior differences between experimental and control situations, and for effectiveness and perceptions. In three experiments paired t-tests were the analysis tool with controls being a no relevance feedback system, a standard ranking for automatic expansion system, and a standard ranking for interactive expansion while the experimental systems based ranking upon user information on temporal relevance and partial relevance. Two further experiments compare using user behavior (number assessed relevant and similarity of relevant documents) to choose a query expansion technique against a non-selective technique and finally the effect of providing the user with knowledge of the process. When partial relevance data and time of assessment data are incorporated in term ranking more relevant documents were recovered in fewer iterations, however retrieval effectiveness overall was not improved. The subjects, none-the-less, rated the suggested terms as more useful and used them more heavily. Explanations of what the feedback techniques were doing led to higher use of the techniques.
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Lalmas, M.; Ruthven, I.: Representing and retrieving structured documents using the Dempster-Shafer theory of evidence : modelling and evaluation (1998)
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Reid, J.; Lalmas, M.; Finesilver, K.; Hertzum, M.: Best entry points for structured document retrieval : part I: characteristics (2006)
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Crestani, F.; Dominich, S.; Lalmas, M.; Rijsbergen, C.J.K. van: Mathematical, logical, and formal methods in information retrieval : an introduction to the special issue (2003)
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- Date
- 22. 3.2003 19:27:36
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Arapakis, I.; Lalmas, M.; Ceylan, H.; Donmez, P.: Automatically embedding newsworthy links to articles : from implementation to evaluation (2014)
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Arapakis, I.; Lalmas, M.; Cambazoglu, B.B.; MarcosM.-C.; Jose, J.M.: User engagement in online news : under the scope of sentiment, interest, affect, and gaze (2014)
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Arapakis, I.; Cambazoglu, B.B.; Lalmas, M.: On the feasibility of predicting popular news at cold start (2017)
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-
Goyal, N.; Bron, M.; Lalmas, M.; Haines, A.; Cramer, H.: Designing for mobile experience beyond the native ad click : exploring landing page presentation style and media usage (2018)
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- Abstract
- Many free mobile applications are supported by advertising. Ads can greatly affect user perceptions and behavior. In mobile apps, ads often follow a "native" format: they are designed to conform in both format and style to the actual content and context of the application. Clicking on the ad leads users to a second destination, outside of the hosting app, where the unified experience provided by native ads within the app is not necessarily reflected by the landing page the user arrives at. Little is known about whether and how this type of mobile ads is impacting user experience. In this paper, we use both quantitative and qualitative methods to study the impact of two design decisions for the landing page of a native ad on the user experience: (i) native ad style (following the style of the application) versus a non-native ad style; and (ii) pages with multimedia versus static pages. We found considerable variability in terms of user experience with mobile ad landing pages when varying presentation style and multimedia usage, especially interaction between presence of video and ad style (native or non-native). We also discuss insights and recommendations for improving the user experience with mobile native ads.
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Nikolov, D.; Lalmas, M.; Flammini, A.; Menczer, F.: Quantifying biases in online information exposure (2019)
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- Abstract
- Our consumption of online information is mediated by filtering, ranking, and recommendation algorithms that introduce unintentional biases as they attempt to deliver relevant and engaging content. It has been suggested that our reliance on online technologies such as search engines and social media may limit exposure to diverse points of view and make us vulnerable to manipulation by disinformation. In this article, we mine a massive data set of web traffic to quantify two kinds of bias: (i) homogeneity bias, which is the tendency to consume content from a narrow set of information sources, and (ii) popularity bias, which is the selective exposure to content from top sites. Our analysis reveals different bias levels across several widely used web platforms. Search exposes users to a diverse set of sources, while social media traffic tends to exhibit high popularity and homogeneity bias. When we focus our analysis on traffic to news sites, we find higher levels of popularity bias, with smaller differences across applications. Overall, our results quantify the extent to which our choices of online systems confine us inside "social bubbles."
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Ruthven, I.; Lalmas, M.; Rijsbergen, K. van: Combining and selecting characteristics of information use (2002)
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