In the era of circular economies, governments and consumers are increasingly aware of environmental protection, which encourages enterprises to devote more attention to reverse logistics (RL). However, the limited res...
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In the era of circular economies, governments and consumers are increasingly aware of environmental protection, which encourages enterprises to devote more attention to reverse logistics (RL). However, the limited resources and technical limitations of most manufacturing companies have motivated them to outsource their RL activities to professional third-party RL providers (3PRLPs). Optimal 3PRLP selection is instrumentally valuable in RL outsourcing practices because it has the potential to increase enterprises' economic profitability and to improve their long-term development. Generally, 3PRLP selection is treated as a multiple-attribute decision-making (MADM) problem. To this end, this paper aims to build a multi-perspective MADM (MPMADM) framework to offer systematic decision support for enterprises to select the optimal 3PRLPs. Attribute assessments in the proposed framework take the form of generalized comparative linguistic expressions (GCLEs), which can be transformed into hesitant fuzzy linguistic term set (HFLTS) possibility distributions with semanticanalysis in order to enhance information quality and reliability. Expert weights are then assigned in the use of an optimization model based on the correlation consensus measurement. Afterwards, the two-stage aggregation paradigm for computing with HFLTS possibility distributions is used to gather assessments at expert and attribute levels to compile overall assessments of each alternative 3PRLP. Compared with existing studies, our proposal considers environmental and social sustainability for attribute system establishment and introduces GCLEs for 3PRLP selection, which offer greater flexibility for experts to articulate their evaluations. In addition, the two-stage aggregation paradigm eliminates distortion and loss of information and provides decision makers with the capability to control the outcome's precision. Moreover, the proposed expert weight determination approach is conducive to generating reliab
Storytelling, and the delivery of societal narratives, enable human beings to communicate, connect, and understand one another and the world around them. Narratives can be defined as spoken, visual, or written account...
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Storytelling, and the delivery of societal narratives, enable human beings to communicate, connect, and understand one another and the world around them. Narratives can be defined as spoken, visual, or written accounts of interconnected events and actors, generally evolving through some notion of time. Today, information is typically conveyed over online communication mediums, such as social media and blogging websites. Consequently, the act of narrative delivery itself has shifted from simply imparting information through self-contained structures such as books, to more fragmented structures, such as social media websites, where evolving story events are constructed over multiple online sources. Ubiquitous online conversation can manifest into sophisticated narratives that have the potential to influence wide-spread user interpretations of cultural sentiments, attitudes, values, as well as geopolitical events and facts. As a result, narratives are actively being used as strategic tools for shaping local events, promoting collective opinions, and asserting ideologies and propaganda, making them sources of interest for identifying themes, intentions, and goals across multiple communities and potential adversaries. Identifying fragmented narratives, extracting thematic and temporal components that constitute evolving narratives, and locating signs of active rhetoric framing tactics, are difficult to detect and analyze without large-scale automation. This problem can be addressed through the use of natural language understanding technologies. Our goal is to document and discuss methods to efficiently construct, extract, and detect evolving online narratives. The novel contribution of this paper is the formal collation and documentation of such technologies and research areas, as well as extensive discussion on open research challenges and goals in the definition, identification, construction, generation, and representation of online narratives. To our knowledge, there
Art appreciation is often considered highly individual, but research has shown that there is also a shared element, which may be due to shared meanings and associations triggered by artworks. In the current analysis, ...
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Art appreciation is often considered highly individual, but research has shown that there is also a shared element, which may be due to shared meanings and associations triggered by artworks. In the current analysis, we examined semantically based justifications given to aesthetic evaluations of abstract and representational artworks provided by 80 primary schoolchildren, aged 4, 5, 8, and 10 years. Using a computationalsemantic similarity analysis technique (UMBC Ebiquity), the authors found that children showed evidence for shared meaning in response to representational but not abstract art. The effect was present from age 4 through to age 10. In addition, it was found that the presence of semantic elements in the justifications boosted aesthetic appreciation, especially of abstract artworks. This suggests that individually constructed meaning is key to aesthetic appreciation and is, to an extent, independent from the meaning that might be assumed to be inherent in artworks, particularly if it is representational. The authors evaluate their findings in relation to aesthetic and developmental theories and make suggestions for future research. They argue that the current data, alongside calibrating analyses that apply their randomization and semanticanalysis protocol to children's picture naming responses, further demonstrate the robustness of the computationalsemantic similarity analysis method, with great potential for further studies in semantic interpretation of art or other types of stimuli.
Our premise is that an intelligent system should be able to structure all the information that can be obtained from natural language text, and it should do it in such a manner that the structured information be useful...
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ISBN:
(纸本)9781467317146
Our premise is that an intelligent system should be able to structure all the information that can be obtained from natural language text, and it should do it in such a manner that the structured information be useful for further processing. This paper presents an experiment in structuring information from the natural language incomplete descriptions of 101 animals collected from a children's dictionary. The goal of this experiment is to use computational semantic analysis of the natural language descriptions-which are quite heavy in common sense knowledge-and to come up with a hierarchy of and similarities among the described animals, as well as flagging descriptions that are largely inconsistent with other information.
Our premise is that an intelligent system should be able to structure all the information that can be obtained from natural language text, and it should do it in such a manner that the structured information be useful...
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ISBN:
(纸本)9781467317139
Our premise is that an intelligent system should be able to structure all the information that can be obtained from natural language text, and it should do it in such a manner that the structured information be useful for further processing. This paper presents an experiment in structuring information from the natural language incomplete descriptions of 101 animals collected from a children's dictionary. The goal of this experiment is to use computational semantic analysis of the natural language descriptions - which are quite heavy in common sense knowledge - and to come up with a hierarchy of and similarities among the described animals, as well as flagging descriptions that are largely inconsistent with other information.
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