1,602 research outputs found
Web Usage Mining with Evolutionary Extraction of Temporal Fuzzy Association Rules
In Web usage mining, fuzzy association rules that have a temporal property can provide useful knowledge about when associations occur. However, there is a problem with traditional temporal fuzzy association rule mining algorithms. Some rules occur at the intersection of fuzzy sets' boundaries where there is less support (lower membership), so the rules are lost. A genetic algorithm (GA)-based solution is described that uses the flexible nature of the 2-tuple linguistic representation to discover rules that occur at the intersection of fuzzy set boundaries. The GA-based approach is enhanced from previous work by including a graph representation and an improved fitness function. A comparison of the GA-based approach with a traditional approach on real-world Web log data discovered rules that were lost with the traditional approach. The GA-based approach is recommended as complementary to existing algorithms, because it discovers extra rules. (C) 2013 Elsevier B.V. All rights reserved
Pragmatic Languages with Universal Grammars
This paper shows the existence of an equilibrium pragmatic Language with a universal grammar as a coordination device under communication misunderstandings. Such a language plays a key role in achieving efficient outcomes in those Sender-Receiver games where there may exist noisy information transmission. The Language is pragmatic in the sense that the Receiverā best response depends on the context, i.e, on the payoffs and on the initial probability distribution of the states of nature of the underlying game. The Language has a universal grammar because the coding rule does not depend on such specific parameters and can then be applied to any Sender-Receiver game with noisy communication.grammar, pragmatic language, prototypes, separating equilibria
A Generalised Quantifier Theory of Natural Language in Categorical Compositional Distributional Semantics with Bialgebras
Categorical compositional distributional semantics is a model of natural
language; it combines the statistical vector space models of words with the
compositional models of grammar. We formalise in this model the generalised
quantifier theory of natural language, due to Barwise and Cooper. The
underlying setting is a compact closed category with bialgebras. We start from
a generative grammar formalisation and develop an abstract categorical
compositional semantics for it, then instantiate the abstract setting to sets
and relations and to finite dimensional vector spaces and linear maps. We prove
the equivalence of the relational instantiation to the truth theoretic
semantics of generalised quantifiers. The vector space instantiation formalises
the statistical usages of words and enables us to, for the first time, reason
about quantified phrases and sentences compositionally in distributional
semantics
A Comprehensive Star Rating Approach for Cruise Ships Based on Interactive Group Decision Making with Personalized Individual Semantics
This article proposes a comprehensive star rating approach for cruise ships by the combination
of subject and objective evaluation. To do that, it firstly established a index system of star
rating for cruise ships. Then, the modified TOPSIS is adopted to tackle objective data for obtaining
star ratings for basic cruise indicators and service capabilities of cruise ships. Thus, the concept of
distributed linguistic star rating function (DLSRF) is defined to analyze the subjective evaluation from
experts and users. Hence, a novel weight calculation method with interactive group decision making
is presented to assign the importance of the main indicators. Particularly, in order to enable decision
makers to effectively deal with the uncertainty in this star rating process, it adopts the personalized
individual semantics (PIS) model. Finally, data of nine cruise ships is collected to obtain their final
star rating results and some suggestions for improving cruise service capabilities and star indicators
were put forward.National Natural Science Foundation of China (NSFC) 71971135,72001134,72071056
China Scholarship Council 202108310183
Innovative Talent Training Project of Graduate Students in Shanghai Maritime University of China 2021YBR00
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