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Tackling the Poor Assumptions of Naive Bayes Text Classifiers
TLDR
This paper proposes simple, heuristic solutions to some of the problems with Naive Bayes classifiers, addressing both systemic issues as well as problems that arise because text is not actually generated according to a multinomial model.
What do people ask their social networks, and why?: a survey study of status message q&a behavior
TLDR
This paper explores the phenomenon of using social network status messages to ask questions, and presents detailed data on the frequency of this type of question asking, the types of questions asked, and respondents' motivations for asking their social networks rather than using more traditional search tools like Web search engines.
Guidelines for Human-AI Interaction
TLDR
This work proposes 18 generally applicable design guidelines for human-AI interaction that can serve as a resource to practitioners working on the design of applications and features that harness AI technologies, and to researchers interested in the further development of human- AI interaction design principles.
The perfect search engine is not enough: a study of orienteering behavior in directed search
TLDR
A modified diary study is presented that investigated how people performed personally motivated searches in their email, in their files, and on the Web, finding that searching by taking small steps allowed users to specify less of their information need and provided a context in which to understand their results.
Personalizing Search via Automated Analysis of Interests and Activities
TLDR
This research suggests that rich representations of the user and the corpus are important for personalization, but that it is possible to approximate these representations and provide efficient client-side algorithms for personalizing search.
Implicit feedback for inferring user preference: a bibliography
TLDR
Traditional relevance feedback methods require that users explicitly give feedback by specifying keywords, selecting and marking documents, or answering questions about their interests, which can be difficult to collect the necessary data and the effectiveness of explicit techniques can be limited.
Characterizing the influence of domain expertise on web search behavior
TLDR
Large-scale analysis of real-world interactions allows us to understand how expertise relates to vocabulary, resource use, and search task under more realistic search conditions than has been possible in previous small-scale studies.
#TwitterSearch: a comparison of microblog search and web search
TLDR
This paper explores search behavior on the popular microblogging/social networking site Twitter and observes that people search Twitter to find temporally relevant information and information related to people, and the results returned from the different corpora support these different uses.
Information re-retrieval: repeat queries in Yahoo's logs
TLDR
It is demonstrated that changes to search engine results can hinder re-finding, and a way to automatically detect repeat searches and predict repeat clicks is provided.
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