Using a degree of interest model to facilitate ontology navigation

Author(s):  
Tricia d'Entremont ◽  
Margaret-Anne Storey
Keyword(s):  
1997 ◽  
Vol 14 (1) ◽  
pp. 52-85
Author(s):  
Thomas E. Hill

Philosophers have debated for millennia about whether moral requirements are always rational to follow. The background for these debates is often what I shall call “the self-interest model.” The guiding assumption here is that the basic demand of reason, to each person, is that one must, above all, advance one's self-interest. Alternatively, debate may be framed by a related, but significantly different, assumption: the idea that the basic rational requirement is to develop and pursue a set of personal ends in an informed, efficient, and coherent way, whether one's choice of ends is based on self-interested desires or not. For brevity I refer to this as “the coherence-and-efficiency model.” Advocates of both models tend to think that, while it is sufficiently clear in principle what the rational thing to do is, what remains in doubt is whether it is always rational to be moral. They typically assume that morality is concerned, entirely or primarily, with our relations to others, especially with obligations that appear to require some sacrifice or compromise with the pursuit of self-interest.


2017 ◽  
Vol 887 ◽  
pp. 012061
Author(s):  
Junkai Yi ◽  
Yacong Zhang ◽  
Mingyong Yin ◽  
Xianghui Zhao

2013 ◽  
Vol 765-767 ◽  
pp. 998-1002
Author(s):  
Shao Xuan Zhang ◽  
Tian Liu

In view of the present personalized ranking of search results user interest model construction difficult, relevant calculation imprecise problems, proposes a combination of user interest model and collaborative recommendation algorithm for personalized ranking method. The method from the user search history, including the submit query, click the relevant webpage information to train users interest model, then using collaborative recommendation algorithm to obtain with common interests and neighbor users, on the basis of these neighbors on the webpage and webpage recommendation level associated with the users to sort the search results. Experimental results show that: the algorithm the average minimum precision than general sorting algorithm was increased by about 0.1, with an increase in the number of neighbors of the user, minimum accuracy increased. Compared with other ranking algorithms, using collaborative recommendation algorithm is helpful for improving webpage with the user interest relevance precision, thereby improving the sorting efficiency, help to improve the search experience of the user.


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