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Proceedings ArticleDOI

Towards a theory model for product search

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TLDR
A theory model for product search based on expected utility theory from economics is proposed, in which the top ranked products are the "best value for money" for a specific user.
Abstract
With the growing pervasiveness of the Internet, online search for products and services is constantly increasing. Most product search engines are based on adaptations of theoretical models devised for information retrieval. However, the decision mechanism that underlies the process of buying a product is different than the process of locating relevant documents or objects.We propose a theory model for product search based on expected utility theory from economics. Specifically, we propose a ranking technique in which we rank highest the products that generate the highest surplus, after the purchase. In a sense, the top ranked products are the "best value for money" for a specific user. Our approach builds on research on "demand estimation" from economics and presents a solid theoretical foundation on which further research can build on. We build algorithms that take into account consumer demographics, heterogeneity of consumer preferences, and also account for the varying price of the products. We show how to achieve this without knowing the demographics or purchasing histories of individual consumers but by using aggregate demand data. We evaluate our work, by applying the techniques on hotel search. Our extensive user studies, using more than 15,000 user-provided ranking comparisons, demonstrate an overwhelming preference for the rankings generated by our techniques, compared to a large number of existing strong state-of-the-art baselines.

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Citations
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The impact of online user reviews on hotel room sales [Summary]

Q. Ye, +2 more
TL;DR: Wang et al. as discussed by the authors developed a fixed effect log-linear regression model to assess the influence of online reviews on the number of hotel room bookings, which indicated a significant relationship between online consumer reviews and business performance of hotels.
Proceedings Article

What's the right price? pricing tasks for finishing on time

TL;DR: It is argued that a pricing policy can be based on the trade-off between price and desired completion time and it is shown how this duality can lead to a better pricing policy for tasks in online labor markets.
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Travel Recommendation by Mining People Attributes and Travel Group Types From Community-Contributed Photos

TL;DR: The experiments confirm that people attributes of individuals and groups are promising and orthogonal to prior works using travel logs only and can further improve prior travel recommendation methods especially for difficult predictions by further leveraging user contexts via mobile devices.
Journal ArticleDOI

The Impact of Fake Reviews on Online Visibility: A Vulnerability Assessment of the Hotel Industry

TL;DR: It is found that even limited injections of fake reviews can have a significant effect and the factors that contribute to this can be explored.
Proceedings ArticleDOI

On Application of Learning to Rank for E-Commerce Search

TL;DR: In this article, the authors discuss the practical challenges in applying learning to rank methods to E-Com search, including the challenges in feature representation, obtaining reliable relevance judgments, and optimally exploiting multiple user feedback signals such as click rates, add-to-cart ratios, order rates, and revenue.
References
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Proceedings Article

Opinion Mining using Econometrics: A Case Study on Reputation Systems

TL;DR: Econometrics is used to identify the “economic value of text” and assign a “dollar value” to each opinion phrase, measuring sentiment effectively and without the need for manual labeling, and argues that by interpreting opinions using econometricrics, it has the first objective, quantifiable, and contextsensitive evaluation of opinions.
Book ChapterDOI

Multi-objective query processing for database systems

TL;DR: This work presents a novel algorithm for computing sets of objects that are nondominated with respect to a set of monotonic objective functions and shows how the response behavior can be improved by progressively producing result objects as quickly as possible, while the algorithm is still running.
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Ranking refinement and its application to information retrieval

TL;DR: This work presents a novel boosting framework for ranking refinement that can effectively leverage the uses of the two sources of information and significantly outperforms the baseline algorithms that incorporate the outputs from the base ranker as an additional feature.
Journal ArticleDOI

A Hybrid Discrete Choice Model of Differentiated Product Demand with an Application to Personal Computers

TL;DR: In this paper, a new discrete choice model of differentiated product demand was proposed that combines the pure characteristics demand model and the random coefficient logit demand model, where consumers were exposed to an idiosyncratic taste shock when they make a brand choice but free from it when they made a product choice within a brand.
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Webpage understanding: beyond page-level search

TL;DR: This paper introduces the webpage understanding problem which consists of three subtasks: webpage segmentation, webpage structure labeling, and webpage text segmentation and labeling.
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