Titlebook: E-Commerce and Web Technologies; 15th International C Martin Hepp,Yigal Hoffner Conference proceedings 2014 Springer International Publishi

松驰

https://doi.org/10.1007/978-981-13-6776-2vative components, including: a ., i.e., a brief and entertaining questionnaire used by the system to learn users’ personality; an . module that acquires ratings-in-context for POIs that users are likely to have experienced; and a . based recommendation module that leverages the personality informat

Cuisine

d-user, Content-based (CB) RSs need both to harvest as much information as possible about such items and to effectively handle it. The boom of . datasets with their huge amount of semantically interrelated data is thus a great opportunity for boosting CB-RSs. In this paper we present a CB-RS that le

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听写

https://doi.org/10.1007/978-3-030-18206-9ction accuracy. However, not all of the ratings bring the same amount of information about the user’s tastes. Active Learning aims at identifying rating data that better reflects users’ preferences. Active learning . are used to selectively choose the items to present to the user in order to acquire

archenemy

Data Banks for Climatological Purposes address situations of user preference scarcity. Through empirical experiments on a multi-domain dataset obtained from Facebook, we show that the proposed personality-aware collaborative filtering methods effectively –and consistently in the studied domains– increase recommendation performance, in t

RACE

Conjuction

Rong Liu,Hongchen Ji,Ruiquan Zhoue. In this study we evaluate the performance of two text-based features that have not been used in that context, namely (a) a variation of the bigram feature, utilizing grammatical dependencies and (b) discourse connectives. By treating helpfulness prediction as a binary classification task we show

玩笑

MAL

Cerebrospinal Fluid (CSF) Scintigraphy,is no longer productive for researchers. We pose a theoretical argument for resolving the confusion of terminology and definitions of digital services, by inductively developing a taxonomy of digital service types, using techniques such as metaphor analysis that are relevant to multiple disciplines.

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