Design and Development of a Query Graph Visualization System

Dion Hoe-Lian Goh; Chel Sian Lee; Chua, Alton Y. K.; Luyt, Brendan
February 2009
Journal of Digital Information Management;Feb2009, Vol. 7 Issue 1, p22
Academic Journal
Collaborative querying is a technique that harnesses the collective search experiences of users to assist in query formulation. We present the Query Graph Visualizer (QGV), a visual collaborative querying system that recommends related queries to a user's submitted query through a network visualization scheme. Users are able to explore the query network and select queries for execution on an information retrieval (IR) system. The QGV is not meant to be a replacement for IR systems but as a value-added module to help users search more effectively. Consequently, the QGV is not an IR system but works in tandem with existing IR systems. The design of the QGV is discussed, focusing on its architecture, the interaction between the QGV's main components and the implementation of the user interface. An evaluation of the QGV was also conducted to assess the performance of the system against to a conventional search engine. Results indicate that the evaluators who used the QGV completed their tasks much faster compared to those using a search engine alone. A usability evaluation also showed that the system complied with standard user interface heuristics.


Related Articles

  • Time heuristics ranking approach for recommended queries using search engine query logs. UMAGANDHI, R.; SENTHIL KUMAR, A. V. // Kuwait Journal of Science;2014, Vol. 41 Issue 2, p127 

    It is obvious that web search queries given by the user are always short and ambiguous. Mostly the shorter length queries do not satisfy the users real information need and may not produce the results properly. Query Recommendation is a technique based on the real intent of the user and to...

  • GET INSPIRED: A VISUAL DIVIDE AND CONQUER APPROACH FOR MOTIVE-BASED SEARCH SCENARIOS. Both, Andreas; Nguyen, Viet; Keck, Mandy; Kammer, Dietrich; Groh, Rainer; Henkens, Dana // Proceedings of the IADIS International Conference on WWW/Interne;2014, p91 

    A novel generation of (e.g. touch-driven) applications leads to a new universe of interaction paradigms and a growing need for simple, inspiring and smart interfaces. A system intended for non-experts should only present information the user needs to solve his task, instead of confronting him...

  • Complex Network Optimization Research of Personalization-based Recommendation Algorithm. GAO Caixia; QI Changping // Advanced Materials Research;7/24/2014, Vol. 989-994, p1441 

    Application value of a variety of complex network makes it become an important scientific research challenges. Therefore, in order to more thoroughly understand the network of human life, we need to further study the properties of the complex network. Complex network search theory solves many...

  • Linking OpenCourseWares and Open Education Resources: Creating an Effective Search and Recommendation System. Shelton, Brett E.; Duffin, Joel; Wang, Yuxuan; Ball, Justin // World Academy of Science, Engineering & Technology;Jun2010, Issue 42, p316 

    No abstract available.

  • A Personalization Recommendation Method Based on Deep Web Data Query. Tao Tan; Hongjun Chen // Journal of Computers;Jul2012, Vol. 7 Issue 7, p1599 

    Deep Web is becoming a hot research topic in the area of database. Most of the existing researches mainly focus on Deep Web data integration technology. Deep Web data integration can partly satisfy people's needs of Deep Web information search, but it cannot learn users' interest, and people...

  • SMART: Semantic multidimensional group recommendations. Ben Ahmed, Eya; Tebourski, Wafa; Ben Abdessalem Karaa, Wahiba; Gargouri, Faïez // Multimedia Tools & Applications;Dec2015, Vol. 74 Issue 23, p10419 

    The rising availability of data in the information systems has boosted the challenging problem of queries recommendation, especially in OLAP systems. In this paper, we introduce an innovative 퓢ℳ퓐퓡퓣 system for semantic multidimensional group recommendations to...

  • A theoretical model for the automatic generation of tag clouds. Torres-Parejo, Ursula; Campaña, Jesús; Vila, M.; Delgado, Miguel // Knowledge & Information Systems;Aug2014, Vol. 40 Issue 2, p315 

    This paper presents a new approach to information retrieval from non-structured attributes in databases, which involves the processing of text attributes. To make retrieval more effective, frequent text sequences are extracted and mathematically represented as intermediate forms which permit a...

  • A Film Retrieval Method based on Ontology. Chi Zhang; Ying Li; Peng Zhou Zhang // Applied Mechanics & Materials;2014, Vol. 713-715, p2409 

    We propose a film retrieval method based on ontology. This method can realize automatically recommendation when users query film resources, even though not giving search keywords explicitly. In this paper, we represent the film retrieval method and film ontology model. And then we define several...

  • Visualization in Argument Based Recommender System. Preeti; Rajpal, Ankit; Khurana, Purnima // International Journal of Computer Science & Information Technolo;2014, Vol. 5 Issue 2, p1352 

    Recommender systems are information filters which are being used to overcome the problem of information overload. The opinion of other users of the system is used to help individuals identify the item which might be of their interest or relevant to their needs. Visualization in Recommender...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics