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ABSTRACT
Many research efforts are addressing the problem of enabling automatic summarization of opinions and assessments stated on the web in product reviews, discussion forums, and blogs. One key difficulty is that relevant assessments scattered throughout web pages are obscured by variations in natural language. In this paper, we focus on a novel aspect of enabling aggregations of assessments of degree to which a given property holds for a given entity (for instance, how touristy is Boston). We present GrainPile, a user interface for extracting from the web, aggregating and quantifying degree assessments of unconstrained topics. The interface provides a variety of functions: a) identification of dimensions of comparison (properties) relevant to a particular entity or set of entities, b) comparisons of like entities on user-specified properties (for example, which university is more prestigious, Yale or Cornell), c) tracing the derived opinions back to their sources (so that the reasons for the opinions can be found). A central contribution in GrainPile is the evaluated demonstration of feasibility of mapping the recognized expressions (such as fairly, very, extremely, and so on) to a common scale of numerical values and aggregating across all the extracted assessments to derive an overall assessment of degree. GrainPile's novel assessment and aggregation of degree expressions is shown to strongly outperform an interpretation-free, co-occurrence based method.
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Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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REVIEW
"Rosziati Ibrahim : Reviewer"
Chklovski presents a case study focused on extracting information for the degree expressions of unconstrained topics found on the Web using a system called GrainPile. GrainPile accepts queries consisting of one or more topics. The system's assessm
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