A User-Centered Concept Mining System for Query and Document Understanding at Tencent

Concepts embody the knowledge of the world and facilitate the cognitive processes of human beings. Mining concepts from web documents and constructing the corresponding taxonomy are core research problems in text understanding and support many downstream tasks such as query analysis, knowledge base construction, recommendation, and search. However, we argue that most prior studies extract formal and overly general concepts from Wikipedia or static web pages, which are not representing the user perspective. In this paper, we describe our experience of implementing and deploying ConcepT in Tencent QQ Browser. It discovers user-centered concepts at the right granularity conforming to user interests, by mining a large amount of user queries and interactive search click logs. The extracted concepts have the proper granularity, are consistent with user language styles and are dynamically updated. We further present our techniques to tag documents with user-centered concepts and to construct a topic-concept-instance taxonomy, which has helped to improve search as well as news feeds recommendation in Tencent QQ Browser. We performed extensive offline evaluation to demonstrate that our approach could extract concepts of higher quality compared to several other existing methods. Our system has been deployed in Tencent QQ Browser. Results from online A/B testing involving a large number of real users suggest that the Impression Efficiency of feeds users increased by 6.01% after incorporating the user-centered concepts into the recommendation framework of Tencent QQ Browser.Comment: Accepted by KDD 201

Second language learning in the context of MOOCs

Massive Open Online Courses are becoming popular educational vehicles through which universities reach out to non-traditional audiences. Many enrolees hail from other countries and cultures, and struggle to cope with the English language in which these courses are invariably offered. Moreover, most such learners have a strong desire and motivation to extend their knowledge of academic English, particularly in the specific area addressed by the course. Online courses provide a compelling opportunity for domain-specific language learning. They supply a large corpus of interesting linguistic material relevant to a particular area, including supplementary images (slides), audio and video. We contend that this corpus can be automatically analysed, enriched, and transformed into a resource that learners can browse and query in order to extend their ability to understand the language used, and help them express themselves more fluently and eloquently in that domain. To illustrate this idea, an existing online corpus-based language learning tool (FLAX) is applied to a Coursera MOOC entitled Virology 1: How Viruses Work, offered by Columbia University

FLAX: Flexible and open corpus-based language collections development

In this case study we present innovative work in building open corpus-based language collections by focusing on a description of the opensource multilingual Flexible Language Acquisition (FLAX) language project, which is an ongoing example of open materials development practices for language teaching and learning. We present language-learning contexts from across formal and informal language learning in English for Academic Purposes (EAP). Our experience relates to Open Educational Resource (OER) options and Practices (OEP) which are available for developing and distributing online subject-specific language materials for uses in academic and professional settings. We are particularly concerned with closing the gap in language teacher training where competencies in materials development are still dominated by print-based proprietary course book publications. We are also concerned with the growing gap in language teaching practitioner competencies for understanding important issues of copyright and licencing that are changing rapidly in the context of digital and web literacy developments. These key issues are being largely ignored in the informal language teaching practitioner discussions and in the formal research into teaching and materials development practices

Investigating an open methodology for designing domain-specific language collections

With this research and design paper, we are proposing that Open Educational Resources (OERs) and Open Access (OA) publications give increasing access to high quality online educational and research content for the development of powerful domain-specific language collections that can be further enhanced linguistically with the Flexible Language Acquisition System (FLAX, http://flax.nzdl.org). FLAX uses the Greenstone digital library system, which is a widely used open-source software that enables end users to build collections of documents and metadata directly onto the Web (Witten, Bainbridge, & Nichols, 2010). FLAX offers a powerful suite of interactive text-mining tools, using Natural Language Processing and Artificial Intelligence designs, to enable novice collections builders to link selected language content to large pre-processed linguistic databases. An open methodology trialed at Queen Mary University of London in collaboration with the OER Research Hub at the UK Open University demonstrates how applying open corpus-based designs and technologies can enhance open educational practices among language teachers and subject academics for the preparation and delivery of courses in English for Specific Academic Purposes (ESAP)

Text categorization and similarity analysis: similarity measure, literature review

Document classification and provenance has become an important area of computer science as the amount of digital information is growing significantly. Organisations are storing documents on computers rather than in paper form. Software is now required that will show the similarities between documents (i.e. document classification) and to point out duplicates and possibly the history of each document (i.e. provenance). Poor organisation is common and leads to situations like above. There exists a number of software solutions in this area designed to make document organisation as simple as possible. I'm doing my project with Pingar who are a company based in Auckland who aim to help organise the growing amount of unstructured digital data. This reports analyses the existing literature in this area with the aim to determine what already exists and how my project will be different from existing solutions