1,721,054 research outputs found
The Inappropriate Use of the PICC to Interpret Hardship Claims under the CISG
This paper comments on a recent decision rendered by the French Supreme Court, which upheld a decision imposing a duty to renegotiate the terms of the contract as a result of a supervening change of circumstnces. Although this approach is not isolated and a comparative account is provided of other legal instruments (national and supranational) and court decisions adpting a similar approach, the authors take a critical position, primarily based on an economic analysis of the consequences of the rule in question
Categorization of Web users by fuzzy clustering
Categorization of users is a fundamental task inWeb personalization. Fuzzy clustering is a valid approach to derive user categories by capturing similar user interests from web usage data available in log files. Usually, fuzzy clustering is based on the use of Euclidean metrics to evaluate similarity between user preferences. This can lead to user categories that do not capture the semantic information incorporated in the original Web usage data. To better capture similarity between users, in this paper we propose the use of a measure that is based on the evaluation of similarity between fuzzy sets. The proposed fuzzy measure is employed in a relational fuzzy clustering algorithm to discover clusters embedded in the Web usage data and derive categories modeling the preferences of similar users. An application example on usage data extracted from log files of a real Web site is reported and a comparison with
the results obtained using the cosine measure is shown to demonstrate the effectiveness of the fuzzy similarity measure
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Replicating features of natural discourse in the preparation of dialogues for B1 learners
ISSN 2038-795
Modelling of Ca2+-promoted structural effects in wild type and post-translationally modified Connexin26
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Newer: a system for neuro-fuzzy web recommendation
In the era of the Web, there is urgent need for developing systems able to personalize the online experience of Web users on the basis of their needs. Web recommendation is a promising technology that attempts to predict the interests of Web users, by providing them with information and/or services that they need without explicitly asking for them. In this paper we propose NEWER, a usage-based Web recommendation system that exploits the potential of Computational Intelligence techniques to dynamically suggest interesting pages to users according to their preferences. NEWER employs a neuro-fuzzy approach in order to determine categories of users sharing similar interests and to discover a recommendation model as a set of fuzzy rules expressing the associations between user categories and relevances of pages. The discovered model is used by a online recommendation module to determine the list of links judged relevant for users. The results obtained on both synthetic and real-world data show that NEWER is effective for recommendation, leading to a quality of the generated recommendations comparable and often significantly better than those of other approaches employed for the comparison
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