Content or context? Searching for musical meaning in task-based interactive information retrieval

Creative professionals search for digital music to accompany moving images using interactive information retrieval systems run by music publishers and record companies. This research investigates the creative professionals and the intermediaries communication processes and information seeking and use behaviour with a view to making recommendations to information retrieval systems builders as to the extent of relative importance of content and contextual factors. A communications model is used to suggest that the meaning of music is determined by its listener and use context, as well as cultural codes and competences. The research is framed by a holistic approach based on Ingwersen and Jarvelin’s Interactive Information Seeking, Retrieval and Behavioral processes model

Spoken query processing for interactive information retrieval

It has long been recognised that interactivity improves the effectiveness of information retrieval systems. Speech is the most natural and interactive medium of communication and recent progress in speech recognition is making it possible to build systems that interact with the user via speech. However, given the typical length of queries submitted to information retrieval systems, it is easy to imagine that the effects of word recognition errors in spoken queries must be severely destructive on the system's effectiveness. The experimental work reported in this paper shows that the use of classical information retrieval techniques for spoken query processing is robust to considerably high levels of word recognition errors, in particular for long queries. Moreover, in the case of short queries, both standard relevance feedback and pseudo relevance feedback can be effectively employed to improve the effectiveness of spoken query processing

Evaluating the implicit feedback models for adaptive video retrieval

Interactive video retrieval systems are becoming popular. On the one hand, these systems try to reduce the effect of the semantic gap, an issue currently being addressed by the multimedia retrieval community. On the other hand, such systems enhance the quality of information seeking for the user by supporting query formulation and reformulation. Interactive systems are very popular in the textual retrieval domain. However, they are relatively unexplored in the case of multimedia retrieval. The main problem in the development of interactive retrieval systems is the evaluation cost.The traditional evaluation methodology, as used in the information retrieval domain, is not applicable. An alternative is to use a user-centred evaluation methodology. However, such schemes are expensive in terms of effort, cost and are not scalable. This problem gets exacerbated by the use of implicit indicators, which are useful and increasingly used in predicting user intentions. In this paper, we explore the effectiveness of a number of interfaces and feedback mechanisms and compare their relative performance using a simulated evaluation methodology. The results show the relatively better performance of a search interface with the combination of explicit and implicit features

Reflections on Mira : interactive evaluation in information retrieval

Evaluation in information retrieval (IR) has focussed largely on noninteractive evaluation of text retrieval systems. This is increasingly at odds with how people use modern IR systems: in highly interactive settings to access linked, multimedia information. Furthermore, this approach ignores potential improvements through better interface design. In 1996 the Commission of the European Union Information Technologies Programme, funded a three year working group, Mira, to discuss and advance research in the area of evaluation frameworks for interactive and multimedia IR applications. Led by Keith van Rijsbergen, Steve Draper and myself from Glasgow University, this working group brought together many of the leading researchers in the evaluation domain from both the IR and human computer interaction (HCI) communities. This paper presents my personal view of the main lines of discussion that took place throughout Mira: importing and adapting evaluation techniques from HCI, evaluating at different levels as appropriate, evaluating against different types of relevance and the new challenges that drive the need for rethinking the old evaluation approaches. The paper concludes that we need to consider more varied forms of evaluation to complement engine evaluation

INTERACTIVE INFORMATION RETRIEVAL: AN OVERVIEW

Information Retrieval (IR) is deal as the interface between the information handler and the framework and the query thus formulated is matched against a keyword indexed in the system whereas in Interactive Information Retrieval (IIR) Human Computer Interaction (HCI) is involved. Although, Interactive Information Retrieval (IIR) is a multidisciplinary field its broad subject is Computer science. Algorithmic kind of IR is still prevalent in Interactive Information Retrieval (IIR), information seeking and information behavior

Theory-based user modeling for personalized interactive information retrieval

In an effort to improve users’ search experiences during their information seeking process, providing a personalized information retrieval system is proposed to be one of the effective approaches. To personalize the search systems requires a good understanding of the users. User modeling has been approved to be a good method for learning and representing users. Therefore many user modeling studies have been carried out and some user models have been developed. The majority of the user modeling studies applies inductive approach, and only small number of studies employs deductive approach. In this paper, an EISE (Extended Information goal, Search strategy and Evaluation threshold) user model is proposed, which uses the deductive approach based on psychology theories and an existing user model. Ten users’ interactive search log obtained from the real search engine is applied to validate the proposed user model. The preliminary validation results show that the EISE model can be applied to identify different types of users. The search preferences of the different user types can be applied to inform interactive search system design and development

Exploring a Multidimensional Representation of Documents and Queries (extended version)

In Information Retrieval (IR), whether implicitly or explicitly, queries and documents are often represented as vectors. However, it may be more beneficial to consider documents and/or queries as multidimensional objects. Our belief is this would allow building "truly" interactive IR systems, i.e., where interaction is fully incorporated in the IR framework. The probabilistic formalism of quantum physics represents events and densities as multidimensional objects. This paper presents our first step towards building an interactive IR framework upon this formalism, by stating how the first interaction of the retrieval process, when the user types a query, can be formalised. Our framework depends on a number of parameters affecting the final document ranking. In this paper we experimentally investigate the effect of these parameters, showing that the proposed representation of documents and queries as multidimensional objects can compete with standard approaches, with the additional prospect to be applied to interactive retrieval