Designing Ranking System for Chinese Product Search Engine Based on Customer Reviews

With the spread of e-commerce platforms, it becomes extremely difficult for the costumer to choose the right product from a large number of products, and different sellers based only on his/her own experience, product picture and meta-data. Customer’s reviews present a rich source of information that have an enormous impact on the purchasing decision of the potential consumers, but reading all of the available reviews is a hard task and time consuming. Thus, the automated mining of these reviews and extract product features in order to generate a raking system present a valuable and useful tool for consumers to make well-versed decision. In this paper, we propose a product search ranking mechanism based on costumers reviews written in Chinese language. We score each product using the features extracted from the reviews. Also, a ranking function has been developed. The proposed research evaluated using customer reviews of two famous brands of mobile phones: Apple and Samsung from taobao.com. The evaluation shows a promising result compared to the existing systems

HOW CAN PRODUCT TEXT SNIPPETS BENEFIT FROM ONLINE CUSTOMER REVIEWS?

Product text snippets should highlight the product features that are appealing to customers. Nevertheless, the features in current product snippets mainly are often decided based on the understanding of vendors or advertisers, and may fail to contain the features appealing to customers. This paper investigates how product text snippets generation can benefit from online customer reviews. In doing so, an automated method is designed, in which features and the opinions are extracted from online reviews, and are further used for product text snippet generation. To verify the effectiveness of the proposed method, we conduct two experiments and the results show that the extracted features and the snippet are effective in inviting potential customers, compared with the baseline ones. Experimental results demonstrate that 1) the extracted features are more appealing to customers; and 2) the snippets generated based on the extracted features are more likely to be clicked

The Impact of Positive Online Review Tags on Snacks Sales: A Case of Bestore in Tmall

Customers’ reviews in e-commerce sites play a significant role in influencing potential customers’ purchasing decisions which ultimately affects products sales. Chinese e-commerce sites like Tmall, Taobao and JD.com contain a collection of aspect tags that group reviews with similar comments tags to help customers browse reviews and evaluate products more conveniently. To validate whether these tags are useful and actually playing a role in promoting future sales, we collected data including product information and review tags on a regular basis for consecutive 8 weeks from Bestore, a snack seller on Tmall. We classified the collected review tags into 9 types based on their semantic meanings. Finally, we analyzed and performed generalized estimating equations (GEE) modeling on the data set consisting of 234 products with a total of 734 tags. The results show that most of the aspect tags are related to immediate period sales volume and certain tags are more capable of nowcasting next immediate sales

Search engine bias: the structuration of traffic on the World-Wide Web

Search engines are essential components of the World Wide Web; both commercially and in terms of everyday usage, their importance is hard to overstate. This thesis examines the question of why there is bias in search engine results – bias that invites users to click on links to large websites, commercial websites, websites based in certain countries, and websites written in certain languages. In this thesis, the historical development of the search engine industry is traced. Search engines first emerged as prototypical technological startups emanating from Silicon Valley, followed by the acquisition of search engine companies by major US media corporations and their development into portals. The subsequent development of pay-per-click advertising is central to the current industry structure, an oligarchy of virtually integrated companies managing networks of syndicated advertising and traffic distribution. The study also shows a global landscape in which search production is concentrated in and caters for large global advertising markets, leaving the rest of the world with patchy and uneven search results coverage. The analysis of interviews with senior search engine engineers indicates that issues of quality are addressed in terms of customer service and relevance in their discourse, while the analysis of documents, interviews with search marketers, and participant observation within a search engine marketing firm showed that producers and marketers had complex relationships that combine aspects of collaboration, competition, and indifference. The results of the study offer a basis for the synthesis of insights of the political economy of media and communication and the social studies of technology tradition, emphasising the importance of culture in constructing and maintaining both local structures and wider systems. In the case of search engines, the evidence indicates that the culture of the technological entrepreneur is very effective in creating a new megabusiness, but less successful in encouraging a debate on issues of the public good or public responsibility as they relate to the search engine industry

Wonders Knowledge Portal

In 2002, Wonders Information Co., Ltd., a software company headquartered in Shanghai, China, started building a knowledge management system. The system, called Wonders Knowledge Portal (WKP), appeared to be well intended, well planned, and well designed. Its functionalities seemed useful and should have appealed to employees. Nevertheless, the usage of the system by the employees had been limited, and the company risked wasting its investment in the KMS

E-commerce as a successful strategy of internationalization : Business plan

55 páginasEste trabajo pretende aportar una visión estratégica sobre cuáles son los factores de éxito de una estrategia de comercio electrónico internacional teniendo en cuenta el fenómeno real de la rápida internacionalización de las PYMES y las start-ups denominado Born Global. Esta investigación puede caracterizarse como una integración de la estrategia empresarial, el marketing, los negocios internacionales y el objetivo personal de convertirse en una empresa a gran escala sobre la base del mercado de mascotas y su rendimiento en los mercados nacionales e internacionales. Este trabajo establece una revisión bibliográfica sobre el concepto de comercio electrónico, la diferencia entre negocio electrónico y comercio electrónico, el fenómeno Born Global, la internacionalización de las PYME y Born Global a través del comercio electrónico, y sus factores de éxito aplicados a un plan de negocio estratégico de un modelo de negocio en el sector de las mascotas.This paper aims to provide a strategic vision on what are the success factors of an international e-commerce strategy taking into account the real phenomenon of the rapid internationalization of SMEs and start-ups called Born Global. This research can be characterized as an integration of business strategy, marketing, international business, and the personal goal of becoming a large-scale venture on the basis of the pet market and its performance in domestic and international markets. This paper establishes a literature review on the concept of e-commerce, the difference between E-business and E-commerce, the Born Global phenomenon, the internationalization of SMEs and Born Global through e-commerce, and its success factors applied to a strategic business plan of a business model in the pet industry.Maestría en Gerencia InternacionalMagíster en Gerencia Internaciona

SEMO: a framework for customer social networks analysis based on semantics

The increasing importance of the Internet in most domains has brought about a paradigm change in consumer relations. The influence of Social Networks has entered the Customer Relationship Management domain under the coined term CRM 2.0. In this context, the need to understand and classify the interactions of customers by means of new platforms has emerged as a challenge for both researchers and professionals world-wide. This is the perfect scenario for the use of SEMO, a platform for Customer Social Networks Analysis based on Semantics and emotion mining. The platform benefits from both semantic annotation and classification and text analysis, relying on techniques from the Natural Language Processing domain. The results of the evaluation of the experimental implementation of SEMO reveal a promising and viable platform from a technical perspective.This work is supported by the Spanish Ministry of Industry, Tourism, and Commerce under the EUREKA project SITIO (TSI-020400-2009-148), SONAR2 (TSI-020100-2008-665) and GO2 (TSI-020400-2009-127)Publicad