10 research outputs found

    Making the news interesting: understanding the relationship between familiarity and interest

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    News feeds are an important element of information encountering, feeding our (new) interests but also leading to a state of information overload. Current solutions often select information similar to the user's interests. However, long-term interest in one topic, and being highly familiar with that topic, does not necessarily imply an actual interest response will occur when more of the same topic is selected. This study explores how important familiarity is in predicting an interest response. In a study with 30 subjects, interest was manipulated by topical familiarity using novel stimuli from a popular news source. This study shows, within this context, familiarity is moderately important for an interest response: familiarity does indeed make the news interesting, but only to a certain extent. The results set a baseline for predicting interest during information encountering, indicating familiarity is important, but not the only influential variable a system should consider when selecting information for users

    Making the news interesting: understanding the relationship between familiarity and interest

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    News feeds are an important element of information encountering, feeding our (new) interests but also leading to a state of information overload. Current solutions often select information similar to the user's interests. However, long-term interest in one topic, and being highly familiar with that topic, does not necessarily imply an actual interest response will occur when more of the same topic is selected. This study explores how important familiarity is in predicting an interest response. In a study with 30 subjects, interest was manipulated by topical familiarity using novel stimuli from a popular news source. This study shows, within this context, familiarity is moderately important for an interest response: familiarity does indeed make the news interesting, but only to a certain extent. The results set a baseline for predicting interest during information encountering, indicating familiarity is important, but not the only influential variable a system should consider when selecting information for users

    When complexity becomes interesting

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    How to provide users a positive experience during interaction with information (i.e., the “Information eXperience” (IX)) is still an open question. As a starting point, this work investigates how the emotion of interest can be influenced by modifying the complexity of the information presented to users. The appraisal theory of interest suggests a “sweet spot” where interest will be at its peak: information that is novel and complex yet still comprehensible. This “sweet spot” is approximated using two studies. Study One develops a computational model of textual complexity founded on psycholinguistic theory on processing difficulty. The model was trained and tested on 12,420 articles, achieving a classification performance of 90.87% on two classes of complexity. Study Two puts the model to its ultimate test: Its application to change the user's IX. Using 18 news articles the influence of complexity on interest and its appraisals is unveiled. A structural equation model shows a positive influence of complexity on interest, yet a negative influence of comprehensibility, confirming a seemingly paradoxical relationship between complexity and interest. By showing when complexity becomes interesting, this paper shows how information systems can use the model of textual complexity to construct an interesting IX

    U.S. Bureau of Plant Industry. [Soil survey report] series 1934, no. 21

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    Text describes the area, climate, agricultural history and statistics, soil-survey methods and definitions, soils and crops, land uses and agricultural methods, irrigation, and morphology and genesis of soils of Zavala County, Texas

    A Survey of the Stete of the Art in Dynamic Programming

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    Assessment of recent process analytical technology (PAT) trends : a multiauthor review

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    This multiauthor review article aims to bring readers up to date with some of the current trends in the field of process analytical technology (PAT) by summarizing each aspect of the subject (sensor development, PAT based process monitoring and control methods) and presenting applications both in industrial laboratories and in manufacture e.g. at GSK, AstraZeneca and Roche. Furthermore, the paper discusses the PAT paradigm from the regulatory science perspective. Given the multidisciplinary nature of PAT, such an endeavour would be almost impossible for a single author, so the concept of a multiauthor review was born. Each section of the multiauthor review has been written by a single expert or group of experts with the aim to report on its own research results. This paper also serves as a comprehensive source of information on PAT topics for the novice reader

    Assessment of Recent Process Analytical Technology (PAT) Trends: A Multiauthor Review

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