Research Directions, Challenges and Issues in Opinion Mining

Rapid growth of Internet and availability of user reviews on the web for any product has provided a need for an effective system to analyze the web reviews. Such reviews are useful to some extent, promising both the customers and product manufacturers. For any popular product, the number of reviews can be in hundreds or even thousands. This creates difficulty for a customer to analyze them and make important decisions on whether to purchase the product or to not. Mining such product reviews or opinions is termed as opinion mining which is broadly classified into two main categories namely facts and opinions. Though there are several approaches for opinion mining, there remains a challenge to decide on the recommendation provided by the system. In this paper, we analyze the basics of opinion mining, challenges, pros & cons of past opinion mining systems and provide some directions for the future research work, focusing on the challenges and issues

Natural language processing

Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems

Research and Development Workstation Environment: the new class of Current Research Information Systems

Against the backdrop of the development of modern technologies in the field of scientific research the new class of Current Research Information Systems (CRIS) and related intelligent information technologies has arisen. It was called - Research and Development Workstation Environment (RDWE) - the comprehensive problem-oriented information systems for scientific research and development lifecycle support. The given paper describes design and development fundamentals of the RDWE class systems. The RDWE class system's generalized information model is represented in the article as a three-tuple composite web service that include: a set of atomic web services, each of them can be designed and developed as a microservice or a desktop application, that allows them to be used as an independent software separately; a set of functions, the functional filling-up of the Research and Development Workstation Environment; a subset of atomic web services that are required to implement function of composite web service. In accordance with the fundamental information model of the RDWE class the system for supporting research in the field of ontology engineering - the automated building of applied ontology in an arbitrary domain area, scientific and technical creativity - the automated preparation of application documents for patenting inventions in Ukraine was developed. It was called - Personal Research Information System. A distinctive feature of such systems is the possibility of their problematic orientation to various types of scientific activities by combining on a variety of functional services and adding new ones within the cloud integrated environment. The main results of our work are focused on enhancing the effectiveness of the scientist's research and development lifecycle in the arbitrary domain area.Comment: In English, 13 pages, 1 figure, 1 table, added references in Russian. Published. Prepared for special issue (UkrPROG 2018 conference) of the scientific journal "Problems of programming" (Founder: National Academy of Sciences of Ukraine, Institute of Software Systems of NAS Ukraine

Generating indicative-informative summaries with SumUM

We present and evaluate SumUM, a text summarization system that takes a raw technical text as input and produces an indicative informative summary. The indicative part of the summary identifies the topics of the document, and the informative part elaborates on some of these topics according to the reader's interest. SumUM motivates the topics, describes entities, and defines concepts. It is a first step for exploring the issue of dynamic summarization. This is accomplished through a process of shallow syntactic and semantic analysis, concept identification, and text regeneration. Our method was developed through the study of a corpus of abstracts written by professional abstractors. Relying on human judgment, we have evaluated indicativeness, informativeness, and text acceptability of the automatic summaries. The results thus far indicate good performance when compared with other summarization technologies

Time Aware Knowledge Extraction for Microblog Summarization on Twitter

Microblogging services like Twitter and Facebook collect millions of user generated content every moment about trending news, occurring events, and so on. Nevertheless, it is really a nightmare to find information of interest through the huge amount of available posts that are often noise and redundant. In general, social media analytics services have caught increasing attention from both side research and industry. Specifically, the dynamic context of microblogging requires to manage not only meaning of information but also the evolution of knowledge over the timeline. This work defines Time Aware Knowledge Extraction (briefly TAKE) methodology that relies on temporal extension of Fuzzy Formal Concept Analysis. In particular, a microblog summarization algorithm has been defined filtering the concepts organized by TAKE in a time-dependent hierarchy. The algorithm addresses topic-based summarization on Twitter. Besides considering the timing of the concepts, another distinguish feature of the proposed microblog summarization framework is the possibility to have more or less detailed summary, according to the user's needs, with good levels of quality and completeness as highlighted in the experimental results.Comment: 33 pages, 10 figure