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Title:Pathfinder – an online shopping assistant driven by data mining
Author(s):Gupta, Akshat
Advisor(s):Campbell, Roy H.
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):Data-mining
Text-mining
Reviews
Walmart
Amazon
Product-search
Probability
Word-association
Summary-generation
Related-words
Machine-learning
Information-retrieval
Search-engine
Key-phrase-highlighting
Walmart-application programming interface (API)
Abstract:Online Shopping is a household phrase that has been extremely successful in easing the lives of many people across the globe. Online shoppers spend ample amounts of time and money in buying products that they receive at their doorstep in a matter of a few days or, in some cases, a few hours. However, it is not as easy as it looks. People either have plenty of specifics in their mind before buying a product or are just looking to explore a range of products for a particular goal. This adds another layer on top of time and money spent – effort. PathFinder is a guide that helps shoppers make more informed choices and reach their final product decision faster. It is a hand-in-hand assistant for shoppers that helps them at critical stages of the buying process to ensure that they either reach their specifics without too much research or that they get to explore granular details which they would miss otherwise. Being an online shopping assistant, PathFinder aims to reduce the effort spent by online shoppers and eases up the online product purchasing process even further.
Issue Date:2017-12-04
Type:Text
URI:http://hdl.handle.net/2142/99362
Rights Information:Coypright 2017 Akshat Gupta
Date Available in IDEALS:2018-03-13
Date Deposited:2017-12


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