Visual exploration and retrieval of XML document collections with the generic system X2

This article reports on the XML retrieval system X2 which has been developed at the University of Munich over the last five years. In a typical session with X2, the user first browses a structural summary of the XML database in order to select interesting elements and keywords occurring in documents. Using this intermediate result, queries combining structure and textual references are composed semiautomatically. After query evaluation, the full set of answers is presented in a visual and structured way. X2 largely exploits the structure found in documents, queries and answers to enable new interactive visualization and exploration techniques that support mixed IR and database-oriented querying, thus bridging the gap between these three views on the data to be retrieved. Another salient characteristic of X2 which distinguishes it from other visual query systems for XML is that it supports various degrees of detailedness in the presentation of answers, as well as techniques for dynamically reordering and grouping retrieved elements once the complete answer set has been computed

Visually querying object-oriented databases

Bibliography: pages 141-145.As database requirements increase, the ability to construct database queries efficiently becomes more important. The traditional means of querying a database is to write a textual query, such as writing in SQL to query a relational database. Visual query languages are an alternative means of querying a database; a visual query language can embody powerful query abstraction and user feedback techniques, thereby making them potentially easier to use. In this thesis, we develop a visual query system for ODMG-compliant object-oriented databases, called QUIVER. QUIVER has a comprehensive expressive power; apart from supporting data types such as sets, bags, arrays, lists, tuples, objects and relationships, it supports aggregate functions, methods and sub-queries. The language is also consistent, as constructs with similar functionality have similar visual representations. QUIVER uses the DOT layout engine to automatically layout a query; QUIVER queries are easily constructed, as the system does not constrain the spatial arrangement of query items. QUIVER also supports a query library, allowing queries to be saved, retrieved and shared among users. A substantial part of the design has been implemented using the ODMG-compliant database system O₂, and the usability of the interface as well as the query language itself is presented. Visual queries are translated to OQL, the standard query language proposed by the ODMG, and query answers are presented using O₂ Look. During the course of our investigation, we conducted a user evaluation to compare QUIVER and OQL. The results were extremely encouraging in favour of QUIVER

Accelerating SQL with Complex Visual Querying

This dissertation addresses the usability improvement of a graphical user interface that allows query formulation without using textual query languages, such as SQL. This visual tool, called Aggregates, is provided on the OutSystems Low-Code Development Platform, to formulate data queries, through interaction and manipulation of visual components. Since Aggregates do not support all the existing functionalities of SQL, the OutSys- tems Platform allows users to build queries using this textual query language. Nonethe- less, by evaluating customers’ SQL queries, it was revealed that a considerable subset of the queries written in SQL could have been formulated using the visual tool. The users’ interviews and the results of the SQL queries evaluation have foreseen that the cause of the reduced acceptance of the visual approach, could be the existing usability problems on the interface. Furthermore, the interface is inadequate to build more complex queries, which involve more entities and conditions. Through an iterative design process, this dissertation includes the design, implemen- tation, and evaluation of prototypes with different fidelity levels. The aim is to optimize the effectiveness and efficiency of the process where users communicate to the system what data they intend to extract from the database. Moreover, the readability and com- prehension improvement of the query visual representation is intended, reducing the time and the effort required to understand what data will be gathering from the database. The final implemented interface is currently incorporated on the OutSystems Platform to accelerate the query formulation process without harming the learnability of the system.Esta dissertação apresenta um estudo sobre o melhoramento da usabilidade de uma inter- face gráfica que permite consultar dados sem recorrer a linguagens de consulta textuais, tais como o SQL. A ferramenta visual abordada, denominada Aggregates, está inserida na Plataforma de Desenvolvimento Low-Code OutSystems, de modo a permitir a formula- ção de consultas a bases de dados, através da interação e manipulação de componentes visuais. Tendo em conta que a interface gráfica disponibilizada não suporta todos os tipos de consultas suportadas pelo SQL, os utilizadores podem recorrer a esta linguagem textual para construir as suas pesquisas. No entanto, ao avaliar estas consultas criadas textual- mente em SQL, por clientes da plataforma, percebeu-se que um conjunto considerável de consultas foram construídas usando SQL, embora pudessem ter sido construídas usando a ferramenta visual disponibilizada. Tanto as entrevistas aos utilizadores, como a análise das consultas construídas usando SQL, indicaram que a falta de aceitação do método visual de construção de consultas era causada por problemas de usabilidade na interface. Para além disso, quando as consultas de dados envolvem mais entidades ou condições, os utilizadores sentem dificuldade a usar a interface. Através de um processo de desenho iterativo, esta dissertação apresenta o desenho, im- plementação e avaliação de protótipos com diferentes níveis de fidelidade. Foi optimizada a eficácia e a eficiência do processo de utilização da interface para consultar dados. Além disso, também se melhorou a legibilidade da representação visual da consulta, de modo a diminuir o tempo e esforço necessário para compreender que dados pretendem ser extraídos da base de dados. A implementação final da interface encontra-se atualmente incorporada na Plataforma OutSystems, acelerando o processo de criação de consultas de dados sem dificultar a aprendizagem necessária para utilizar o sistema

Know2Look: Commonsense Knowledge for Visual Search

With the rise in popularity of social media, images accompanied by contextual text form a huge section of the web. However, search and retrieval of documents are still largely dependent on solely textual cues. Although visual cues have started to gain focus, the imperfection in object/scene detection do not lead to significantly improved results. We hypothesize that the use of background commonsense knowledge on query terms can significantly aid in retrieval of documents with associated images. To this end we deploy three different modalities - text, visual cues, and commonsense knowledge pertaining to the query - as a recipe for efficient search and retrieval

Simulated evaluation of faceted browsing based on feature selection

In this paper we explore the limitations of facet based browsing which uses sub-needs of an information need for querying and organising the search process in video retrieval. The underlying assumption of this approach is that the search effectiveness will be enhanced if such an approach is employed for interactive video retrieval using textual and visual features. We explore the performance bounds of a faceted system by carrying out a simulated user evaluation on TRECVid data sets, and also on the logs of a prior user experiment with the system. We first present a methodology to reduce the dimensionality of features by selecting the most important ones. Then, we discuss the simulated evaluation strategies employed in our evaluation and the effect on the use of both textual and visual features. Facets created by users are simulated by clustering video shots using textual and visual features. The experimental results of our study demonstrate that the faceted browser can potentially improve the search effectiveness