A Conceptual Framework for Enhancing Product Search with Product Information from Reviews
2018
- 260Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage260
- Abstract Views164
- Downloads96
Article Description
Product search today is limited, as users can only search and filter for a restricted set of product features, e.g. 15” and 1TB hard disk when searching for a laptop. The often decision- critical aspects of a product are however hidden in user reviews (“noisy fan” or “bright display”) and are not available until a product has been found. This paper proposes a conceptual framework for the integration of product aspects, that have been mined and derived from consumer reviews, into the product search. The framework structures the challenges that arise in four major fields and gives an overview of existing research for each one of them: Data challenges, user experience challenges, purchase process challenges and business challenges. It may inform researchers from various disciplines to perform target-oriented research as well as practitioners what to consider when building up such an enriched product search.
Bibliographic Details
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