COLLATE – A collaboratory supporting research on historic European films

In the COLLATE project, we aim to design and implement a Web-based collaboratory for archives, scientists, and end users working with digitized cultural material. Our example domain is the historic film documentation comprising digitized material about European films of the early 20th century. Designed as a content- and context-based knowledge working environment for distributed user groups, the COLLATE system supports both individual work and collaboration of domain experts who are analyzing, evaluating, indexing, and annotating material in the data repository. The system provides appropriate task-based interfaces for indexing and annotating. As a multifunctional means of in-depth analysis, annotations can be made individually but also collaboratively, for example in the form of annotation of annotations. Combining results from manual and automatic indexing procedures, elaborate content- and context-based information retrieval mechanisms can be applied.     

User-Tailored Planning of Mixed Initiative Information-Seeking Dialogues

Intelligent dialogue systems usually concentrate on user support at the level of the domain of discourse, following a plan-based approach. Whereas this is appropriate for collaborative planning tasks, the situation in interactive information retrieval systems is quite different: there is no inherent plan-goal hierarchy, and users are known to often opportunistically change their goals and strategies during and through interaction. We need to allow for mixed-initiative retrieval dialogues, where the system evaluates the user's individual dialogue behavior and performs situation-dependent interpretation of user goals, to determine when to take the initiative and to change the control of the dialogue, e.g., to propose (new) problem-solving strategies to the user. In this article, we present the dialogue planning component of a concept- oriented, logic-based retrieval system (MIRACLE). Users are guided through the global stages of the retrieval interaction but may depart, at any time, from this guidance and change the direction of the dialogue. When users submit ambiguous queries or enter unexpected dialogue control acts, abductive reasoning is used to generate interpretations of these user inputs in light of the dialogue history and other internal knowledge sources. Based on these interpretations, the system initiates a short dialogue offering the user suitable options and strategies for proceeding with the retrieval dialogue. Depending on the user's choice and constraints resulting from the history, the system adapts its strategy accordingly.