56,191 research outputs found
The contribution of data mining to information science
The information explosion is a serious challenge for current information institutions. On the other hand, data mining, which is the search for valuable information in large volumes of data, is one of the solutions to face this challenge. In the past several years, data mining has made a significant contribution to the field of information science. This paper examines the impact of data mining by reviewing existing applications, including personalized environments, electronic commerce, and search engines. For these three types of application, how data mining can enhance their functions is discussed. The reader of this paper is expected to get an overview of the state of the art research associated with these applications. Furthermore, we identify the limitations of current work and raise several directions for future research
Towards Knowledge-Based Personalized Product Description Generation in E-commerce
Quality product descriptions are critical for providing competitive customer
experience in an e-commerce platform. An accurate and attractive description
not only helps customers make an informed decision but also improves the
likelihood of purchase. However, crafting a successful product description is
tedious and highly time-consuming. Due to its importance, automating the
product description generation has attracted considerable interests from both
research and industrial communities. Existing methods mainly use templates or
statistical methods, and their performance could be rather limited. In this
paper, we explore a new way to generate the personalized product description by
combining the power of neural networks and knowledge base. Specifically, we
propose a KnOwledge Based pErsonalized (or KOBE) product description generation
model in the context of e-commerce. In KOBE, we extend the encoder-decoder
framework, the Transformer, to a sequence modeling formulation using
self-attention. In order to make the description both informative and
personalized, KOBE considers a variety of important factors during text
generation, including product aspects, user categories, and knowledge base,
etc. Experiments on real-world datasets demonstrate that the proposed method
out-performs the baseline on various metrics. KOBE can achieve an improvement
of 9.7% over state-of-the-arts in terms of BLEU. We also present several case
studies as the anecdotal evidence to further prove the effectiveness of the
proposed approach. The framework has been deployed in Taobao, the largest
online e-commerce platform in China.Comment: KDD 2019 Camera-ready. Website:
https://sites.google.com/view/kobe201
Removing the Digital Divide for Senior Web Users
It is hard for the elderly to use the internet to find the resource they want. Usually help is needed for them to complete the task on the technology things. The main reason for this project is to research ideas on encourage senior people to make use of the web to locate helps they want, such as finding volunteers and professional helps. The scope of this project is to develop a new way of web access and content presentation methodologies that let senior people getting help from volunteers and various service providers more easily that incorporates social networking technology e.g. Facebook. By incorporating the social network web site like Facebook into the web application, senior people will be able to find volunteering help or other related service providers through social networking. Volunteers will show up in Google map in search results for senior to easily locate helps. Senior people can also search for self help videos tutorials through the web application search engine. A mobile version of the senior user application will also be developed for easy access on the road. Other features that benefit senior users includes voice input, control / content posting and collaborative social networking where a sponsors would sponsor a help task volunteer undertake
- …