(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 8, No. 9, 2017 217 | Page www.ijacsa.thesai.org Question Answering Systems: A Review on Present Developments, Challenges and Trends Lorena Kodra Department of Computer Engineering Polytechnic University of Tirana Tirana, Albania Elinda Kajo Meçe Department of Computer Engineering Polytechnic University of Tirana Tirana, Albania Abstract—Question Answering Systems (QAS) are becoming a model for the future of web search. In this paper we present a study of the latest research in this area. We collected publications from top conferences and journals on information retrieval, knowledge management, artificial intelligence, web intelligence, natural language processing and the semantic web. We identified and classified the topics of Question Answering (QA) being researched on and the solutions that are being proposed. In this study we also identified the issues being most researched on, the most popular solutions being proposed and the newest trends to help researchers gain an insight on the latest developments and trends of the research being done in the area of question answering. Keywords—Question answering systems; community question answering systems I. INTRODUCTION In this paper we present a study of the latest research being done on question answering systems. We attempt to give an answer to questions like: Are researchers gaining or losing interest in QAS? What are the characteristics of QAS being given most attention to? What are the topics of the research being given most attention to? What are the challenges faced by researchers in this area? What kinds of solutions are being proposed? What are the newest features being applied? What are possible trends of the research in this area? We collected publications from top conferences and journals on information retrieval, knowledge management, artificial intelligence, web intelligence, natural language processing and the semantic web in the last three years and made a quantitative and topic- based analysis of these publications. Our work can be used to help researchers gain an insight on the present state and latest trends of the research being done in the area of question answering systems. Unlike related work [1], [2] that classify and report the state of the art of question answering systems, our study makes a quantitative analysis on the amount of research being done in the area of question answering as well as topic-based classification and research trend identification. To the best of our knowledge this is the first review of QAS from this perspective. The rest of this paper is organized as follows: In Section 2 we describe the methodology used in our study and define objectives and research questions. Section 3 makes a quantitative and topic-based analysis of the collected research. Section 4 discusses the results and conclusions derived from our study. Finally, we list the selected papers in Appendix A. II. METHODOLOGY A. Research Questions As a primary step in the investigation, retrieval and selection of the most accurate publications for our review we have defined the following research questions: RQ1: Are researchers gaining or losing interest in QAS? RQ2: What are the characteristics of QAS being given most attention to? RQ3: What are the topics of the research being given most attention to? RQ4: What are the challenges faced by researchers in this area? RQ5: What kinds of solutions are being proposed? RQ6: What are the trends of research in this area? B. Search Keywords and Source Selection In order to extract the most relevant information for our review we used the following keywords and their combination and synonyms. The search string below was used as a query to search for publications in different online digital libraries: (―Question answering‖ OR ―question answer‖ OR ―question answering system‖ OR ―question answering systems‖). The search for these keywords was done on the title of the publication, as well as the abstract. We selected three of the top scientific digital libraries that represent primary sources for computer science research publications. We did not include online archives Google Scholar and ArXiv because they index content from existing digital libraries. The sources are shown in Table 1. TABLE I. SOURCES SELECTED FOR THE SEARCH PROCESS Source URL IEEExplore http://ieeexplore.ieee.org ACM Digital Library http://dl.acm.org Springer Link http://link.springer.com