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) preferences of the user with respect to a set of keywords. These preferences may then be used to rank the daily news, so that the user is recommended those items that match better with his/her interests. The cyclic preference learning methodology described in this paper is illustrated with a case example based on real news from
of services to various clients by not considering different clients requirements and therefore not able to fulfill clients actualize needs. For this method, we introduce a Positive Negative Keyword-Aware Service Recommendation strategy, abbreviated PNKASR, to minimize the raised difficulties and for accuracy point of
-industrial collaboration with a software company. The collaboration is intended to suggest multiple code fragments to be changed simultaneously when a developer specifies a keyword such as variable names on source code. In the collaboration, we propose to use code clones and logical couplings information to reorder the code
Social networks form an important platform for information sharing and interaction among users. The content from social networks can be used to generate recommendations for users in order to help them to choose what they desire. There exist a lot of recommendation methods currently. In this paper, we propose a keyword
Recently, keyword search on XML data has received much attention. Existing XML keyword search algorithms are all based on Dewey labeling, and this method in the calculation of the common ancestor would suffer from the CAR (common-ancestor-repetition) problem. In this paper, we propose a novel index based on interval
Real-time keywords potentially demonstrate positive effects when they are provided in cross-cultural communication. Previously real-time keywords generated by a speaker during talking were investigated, and it was found it contributes to build mutual understanding and knowledge. However the use of keywords was not
In the last three decades, engineering education research (EER) has made remarkable progress towards a field of interdisciplinary scholarship. This paper defines EER by developing a keyword-based scheme for exploring EER-related scientific publications and collaboration. The keyword-based scheme refers to a conceptual
In general, content-based recommender systems use a keyword vector to locate recommendations. However, this method does not consider relations of each keyword and it is also inscrutable to users, who may have a hard time determining which words in their profiles are important and which may be skewing their results to
In this paper we focus on personalized recommendation algorithm for coupon deals, which are very different from deals of other retailers. We first analyzed some sample deals from Groupon and found that deals under category dining, Wellness and activities have a high probability of having the same keywords in the deal
Search engine marketing provided by search engines enable companies to promote their products to internet users based on their queries is now a major online advertising channel. In most search-based advertising services, advertisers could have dozens of keywords for the same product or service, and in most instances
Keywords of academic papers are jargons shared within a research domain as well as a summary of the contents. However, the increasing popularity of the interdisciplinary research in academia in recent years opened a possibility that the choice of keywords would be no longer confined by the traditional domain
Recommender systems have been widely deployed on E-commerce websites. The cold start problem of making effective recommendations to new users without any historical data on the website is still challenging. These new users often have some available information, such as search keywords, before visiting the website. It
Many misunderstandings can occur during remote interaction due to different user domain competency levels, different cognitive capacity of users as well as different user backgrounds. In this paper, we propose an adaptive keyword/summary presentation approach that aims at identifying potential misunderstandings of
, a collaborative tagging-based environment for Web service discovery, allowing users to tag or annotate a Web service using keyword or free-text. Our system proposes consequently two types of query to search tagged Web services: keyword based and free-text. We put in place an advanced mode in the discovery by keyword
In this paper we derive the non-cooperative, optimal policy towards international R&D cooperation. Two types of R&D cooperation are considered: collaboration and coordination. When firms cooperate, the familiar strategic behavior, which prevails in R&D competition, is reduced, or eliminated, or even completely reversed. However, we prove that R&D subsidy is still an optimal policy...
(e. g. writing summary) and provides more relevant, personalized recommendations. Keyword maps proposed with keywords and various relations among them in this article describe content of each learning object and knowledge of each learner existing. The research hypothesizes that keyword maps should help to increase both
An important and challenging task in any keyword-based search system in text documents or relational databases is the capability of the system to find additional results besides the actual search results and present them to the users as recommendations. This function allows the records that might be of interest to the
Keyword-based search exploits the exact match between the index terms of a query and documents. Thus, some documents, although they are relevant to the given query, may not be returned to users unless the documents include the index terms of the query. Some search engines use the authority of documents, which is
collaboration by stressing, warning, and presenting keywords/summaries in multimedia. Effects of presenting keywords/summaries adaptively depending on situations are evaluated as to the decrease of not-/misunderstanding possibilities during the explanation on the Cyberspace. Moreover, the adaptive selection effects of keywords or
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