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Improving Clustering-based Schema Matching using Latent Semantic Indexing
Partitioning-based Ontology Matching Approaches: A Comparative Analysis
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Recommending Judgment Targets for Rating Provision
Towards Semantic Recommendation of Biodiversity Datasets based on Linked Open Data
Recommending Judgment Targets for Rating Provision
Title: | Recommending Judgment Targets for Rating Provision |
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Authors: | Friederike Klan, Birgitta König-Ries |
Source: | To appear In Proceedings of the 2014 IEEE/WIC/ACM International Conference on Web Intelligence |
Place: | Warsaw, Poland |
Date: | 2014-08-01 |
Type: | Conference Paper |
Abstract: |
Existing rating and reviewing schemes typically come in the in the flavor of a single rating and/or a textual review. While a single judgment evaluating the overall quality of a product is of limited significance, textual customer reviews typically deliver more informative feedback at the attribute level. However, reading and comparing them to extract relevant information is time-consuming and mentally-demanding. Moreover, they are often biased and selective in the product features they consider and thus are less helpful for making informed buying decisions. We therefore propose a rating elicitation scheme that supports consumers in providing meaningful and machine-comprehensible, i.e automatically processable, responses in terms of multi-criteria ratings judging several features of a purchased product or used service. This is achieved by recommending suitable judgment targets and thereby accounting for a customer’s willingness to provide ratings. Our evaluation results show that the proposed procedure effectively adjusts to a consumer’s personal judgment preferences and thus provides helpful support for the elicitation of meaningful multi-criteria feedback. |
File: | klan2014.pdf |