A Survey of Definitions and Models of Exploratory Search

International audienceExploratory search has an unclear and open-ended definition. The complexity of the task and the difficulty of defining this activity are reflected in the limits of existing evaluation methods for exploratory search systems. In order to improve them, we intend to design an evaluation method based on a user-centered model of exploratory search. In this work, we identified and defined the characteristics of exploratory search and used them as an information seeking model evaluation grid. We tested this analytic grid on two information seeking models: Ellis' and Marchionini's models. The results show that Marchonini's model does not match our evaluation method's requirements whereas on the other hand Ellis' model could be adapted to better suit exploratory search

Un Modèle de Recherche Exploratoire pour l'Évaluation de ses Systèmes & Applications

International audienceCurrent evaluation methods of exploratory search systems are still incomplete as they are not fully based on a suitable model of the exploratory search process: as such they cannot be used to determine if they effectively support exploratory search behaviours and tasks. Aiming to elaborate evaluation methods based on an appropriate model of exploratory search, we propose in this paper a model of the exploratory search process compliant with the acknowledged exploratory search characteristics, and we present the first evaluation of this model.Les moteurs de recherche exploratoire sont des systèmes visant à assister le processus d’exploration d’information. Les méthodes actuelles d’évaluation de ces moteurs ne sont pas adaptées pour vérifier s’ils assistent effectivement et complètement les comportements et tâches de recherche exploratoire, car elles ne reposent pas sur un modèle approprié de ces comportements et tâches. Afin d’élaborer des méthodes d’évaluation basées sur une meilleure compréhension du processus d’exploration, nous proposons ici un modèle du processus de recherche exploratoire conforme aux caractéristiques reconnues de processus et présentons une première évaluation de ce modèle

A Model-based Heuristic Evaluation Method of Exploratory Search

International audienceA shortcoming of current evaluation methods of exploratory search engines is that they cannot be used to determine whether users' behaviours and exploratory search tasks are usefully supported. One main reason is that these methods rely on a loosely defined model of the exploratory search process. The aim of this paper is to propose a new model-based heuristic evaluation method of these systems. We present the approach used to design the heuristics of exploratory search and a checklist form for using them. The evaluation of the heuristics and its procedure demonstrates that they significantly help the users achieve an exploratory search system assessment

"Exploratory search" - kłopoty architekta informacji z terminologią

Information environments (co-) designed by information architects should significantly support the users in obtaining information. Using English-language literature as source of examples, the author characterizes user activity type referred to as exploratory search, especially the concept of information foraging, which she suggests calling “traversing information environments”. This article aims at clarifying and organizing Polish terminology related to exploratory practices and user experiences. The analysis of Polish sources on information science of the 21st century evidences the terminological disorder. The author believes that order, precision and terminological consistency are especially needed in the dynamically developing area of information architecture in Poland, especially if treated as an academic discipline. The findings contribute to the theory and methodology of the Polish school of information architecture. The author believes that a constructive discussion of information professionals might be initiated by the proposals presented in this article

Using Knowledge Anchors to Facilitate User Exploration of Data Graphs

YesThis paper investigates how to facilitate users’ exploration through data graphs for knowledge expansion. Our work focuses on knowledge utility – increasing users’ domain knowledge while exploring a data graph. We introduce a novel exploration support mechanism underpinned by the subsumption theory of meaningful learning, which postulates that new knowledge is grasped by starting from familiar concepts in the graph which serve as knowledge anchors from where links to new knowledge are made. A core algorithmic component for operationalising the subsumption theory for meaningful learning to generate exploration paths for knowledge expansion is the automatic identification of knowledge anchors in a data graph (KADG). We present several metrics for identifying KADG which are evaluated against familiar concepts in human cognitive structures. A subsumption algorithm that utilises KADG for generating exploration paths for knowledge expansion is presented, and applied in the context of a Semantic data browser in a music domain. The resultant exploration paths are evaluated in a task-driven experimental user study compared to free data graph exploration. The findings show that exploration paths, based on subsumption and using knowledge anchors, lead to significantly higher increase in the users’ conceptual knowledge and better usability than free exploration of data graphs. The work opens a new avenue in semantic data exploration which investigates the link between learning and knowledge exploration. This extends the value of exploration and enables broader applications of data graphs in systems where the end users are not experts in the specific domain

Intelligent Support for Exploration of Data Graphs

This research investigates how to support a user’s exploration through data graphs generated from semantic databases in a way leading to expanding the user’s domain knowledge. To be effective, approaches to facilitate exploration of data graphs should take into account the utility from a user’s point of view. Our work focuses on knowledge utility – how useful exploration paths through a data graph are for expanding the user’s knowledge. The main goal of this research is to design an intelligent support mechanism to direct the user to ‘good’ exploration paths through big data graphs for knowledge expansion. We propose a new exploration support mechanism underpinned by the subsumption theory for meaningful learning, which postulates that new knowledge is grasped by starting from familiar concepts in the graph which serve as knowledge anchors from where links to new knowledge are made. A core algorithmic component for adapting the subsumption theory for generating exploration paths is the automatic identification of Knowledge Anchors in a Data Graph (KADG). Several metrics for identifying KADG and the corresponding algorithms for implementation have been developed and evaluated against human cognitive structures. A subsumption algorithm which utilises KADG for generating exploration paths for knowledge expansion is presented and evaluated in the context of a semantic data browser in a musical instrument domain. The resultant exploration paths are evaluated in a controlled user study to examine whether they increase the users’ knowledge as compared to free exploration. The findings show that exploration paths using knowledge anchors and subsumption lead to significantly higher increase in the users’ conceptual knowledge. The approach can be adopted in applications providing data graph exploration to facilitate learning and sensemaking of layman users who are not fully familiar with the domain presented in the data graph

Visualisation des résultats de recherche classifiés en contexte de recherche d’information exploratoire : une évaluation d’utilisabilité

La recherche d’information exploratoire sur le Web présente des défis cognitifs en termes de stratégies cognitives et de tactiques de recherche. Le modèle « question-réponse » des moteurs de recherche actuels est inadéquat pour faciliter les stratégies de recherche d’information exploratoire, assimilables aux stratégies cognitives de l’apprentissage. La visualisation des résultats de recherche est un dispositif qui possède des propriétés graphiques et interactives pertinentes pour le traitement de l’information et l’utilisation de la mémoire et, plus largement de la cognition humaine. Plusieurs recherches ont été menées dans ce contexte de recherche d’information exploratoire, mais aucune n’a distinctement isolé le facteur graphique et interactif de la « visualisation » au sein de son évaluation. L’objectif principal de cette thèse est de vérifier si la visualisation des résultats en contexte de recherche d’information exploratoire témoigne des avantages cognitifs et interactifs pressentis selon ses présupposés théoriques. Pour décrire et déterminer la valeur ajoutée de la visualisation des résultats de recherche dans un contexte de recherche d’information exploratoire sur le Web, cette recherche propose de mesurer son utilisabilité. En la comparant selon les mêmes critères et indicateurs à une interface homologue textuelle, nous postulons que l’interface visuelle atteindra une efficacité, efficience et satisfaction supérieure à l’interface textuelle, dans un contexte de recherche d’information exploratoire. Les mesures objectives de l’efficacité et de l’efficience reposent principalement sur l’analyse des traces de l’interaction des utilisateurs, leur nombre et leur durée. Les mesures subjectives attestant de la satisfaction procurée par l’usage du système dans ce contexte repose sur la perception des utilisateurs par rapport à des critères de perception de la facilité d’utilisation et de l’utilité de l’interface testée et par rapport à des questions plus large sur l’expérience de recherche vécue. Un questionnaire et un entretien ont été passés auprès de chacun des vingt-trois répondants. Leur session de recherche a aussi été enregistré par un logiciel de capture vidéo d’écran. Sur les données des vingt-trois utilisateurs divisés en deux groupes, l’analyse statistique a révélé de faibles différences significatives entre les deux interfaces. Selon les mesures effectuées, l’interface textuelle s’est révélée plus efficace en terme de rappel et de pertinence ; et plus efficiente pour les durées de la recherche d’information. Sur le plan de la satisfaction, les interfaces ont été appréciées toutes deux posivitivement, ne permettant pas de les distinguer pour la grande majorité des métriques. Par contre, au niveau du comportement interactif, des différences notables ont montré que les utilisateurs de l’interface visuelle ont réalisé davantage d’interactions de type exploratoire, et ont procédé à une collecte sélective des résultats de recherche. L’analyse statistique et de contenu sur le critère de l’expérience vécue a permis de démontrer que la visualisation offre l’occasion à l’utilisateur de s’engager davantage dans le processus de recherche d’information en raison de l’impact positif de l’esthétique de l’interface visuelle. De plus, la fonctionnalité de classification a été perçue de manière ambivalente, divisant les candidats peu importe l’interface testée. Enfin, l’analyse des verbatims des « visuelle » a permis d’identifier le besoin de fonctionnalités de rétroaction de l’utilisateur afin de pouvoir communiquer le besoin d’information ou sa pondération des résultats ou des classes, grâce à des modalités interactives de manipulation directe des classes sur un espace graphique.Conducting exploratory searches on the web presents a number of cognitive difficulties as regards search strategies and tactics. The “question-response” model used by the available search engines does not respond adequately to exploratory searches, which are akin to cognitive learning strategies. Visualising search results involves graphic and interactive properties for presenting information that are pertinent for processing and using information, as well as for remembering and, more broadly, for human cognition. Many studies have been conducted in the area of exploratory searches, but none have focussed specifically on the graphic and interactive features of visualisation in their analysis. The principal objective of this thesis is to confirm whether the visualisation of results in the context of exploratory searches offers the cognitive and interactive advantages predicted by conjectural theory. In order to describe and to determine the added value of visualising search results in the context of exploratory web searches, the study proposes to measure its usability. By comparing it to a parallel text interface, using the same criteria and indicators, the likelihood of better efficiency, efficacy, and satisfaction when using a visual interface can be established. The objective measures of efficiency and efficacy are based mainly on the analysis of user interactions, including the number of these interactions and the time they take. Subjective measures of satisfaction in using the system in this context are based on user perception regarding ease of use and the usefulness of the interface tested, and on broader questions concerning the experience of using the search interface. These data were obtained using a questionnaire and a discussion with each participant. Statistical analysis of the data from twenty-three participants divided into two groups showed slightly significant differences between the two interfaces. Analysis of the metrics used showed that the textual interface is more efficient in terms of recall and pertinence, and more efficacious concerning the time needed to search for information. Regarding user satisfaction, both interfaces were seen positively, so that no differences emerged for the great majority of metrics used. However, as regards interactive behaviour, notable differences emerged. Participants using the visual interface had more exploratory interaction, and went on to select and collect pertinent search results. Statistical and content analysis of the experience itself showed that visualisation invites the user to become more involved in the search process, because of the positive effect of a pleasing visual interface. In addition, the classification function was perceived as ambivalent, dividing the participants no matter which interface was used. Finally, analysis of the verbatim reports of participants classed as “visual” indicated the need for a user feedback mechanism in order to communicate information needs or for weighting results or classes, using the interactive function for manipulating classes within a geographic space