Post processing of multimedia information - concepts, problems, and techniques

Currently, most research work on multimedia information processing is focused on multimedia information storage and retrieval, especially indexing and content-based access of multimedia information. We consider multimedia information processing should include one more level-post-processing. Here &quot;post-processing&quot; means further processing of retrieved multimedia information, which includes fusion of multimedia information and reasoning with multimedia information to reach new conclusions. In this paper, the three levels of multimedia information processing storage, retrieval, and post-processing- are discussed. The concepts and problems of multimedia information post-processing are identified. Potential techniques that can be used in post-processing are suggested, By highlighting the problems in multimedia information post-processing, hopefully this paper will stimulate further research on this important but ignored topic.<br /

The relationship between IR and multimedia databases

Modern extensible database systems support multimedia data through ADTs. However, because of the problems with multimedia query formulation, this support is not sufficient.\ud \ud Multimedia querying requires an iterative search process involving many different representations of the objects in the database. The support that is needed is very similar to the processes in information retrieval.\ud \ud Based on this observation, we develop the miRRor architecture for multimedia query processing. We design a layered framework based on information retrieval techniques, to provide a usable query interface to the multimedia database.\ud \ud First, we introduce a concept layer to enable reasoning over low-level concepts in the database.\ud \ud Second, we add an evidential reasoning layer as an intermediate between the user and the concept layer.\ud \ud Third, we add the functionality to process the users' relevance feedback.\ud \ud We then adapt the inference network model from text retrieval to an evidential reasoning model for multimedia query processing.\ud \ud We conclude with an outline for implementation of miRRor on top of the Monet extensible database system

Facets and Typed Relations as Tools for Reasoning Processes in Information Retrieval

Faceted arrangement of entities and typed relations for representing different associations between the entities are established tools in knowledge representation. In this paper, a proposal is being discussed combining both tools to draw inferences along relational paths. This approach may yield new benefit for information retrieval processes, especially when modeled for heterogeneous environments in the Semantic Web. Faceted arrangement can be used as a se-lection tool for the semantic knowledge modeled within the knowledge repre-sentation. Typed relations between the entities of different facets can be used as restrictions for selecting them across the facets

User context and personalisation

The importance of user context as a means of delivering personalised and context-sensitive systems is discussed. Relevant aspects of personalisation and context technology are covered. The intention is to inspire those interested in Case-base reasoning and personalisation from background and experience in other disciplines such as information retrieval, adaptive user interfaces, user modelling and mobile computing. Descriptions of personalisation and context are followed by their use in information retrieval and their importance and use in ambient computing. Relevant literature that may be a motivating source for interested readers are provided. Various questions are also raised in initiating discussion on this topic

Query Expansion: Is It Necessary In Textual Case-Based Reasoning?

Query expansion (QE) is the process of transforming a seed query to improve retrieval performance in information retrieval operations. It is often intended to overcome a vocabulary mismatch between the query and the document collection. Query expansion is known to improve retrieval effectiveness of some information retrieval systems, however, its effect in Textual Case-based reasoning (TCBR) which is closely related to the field of Information Retrieval has not been well studied. In this research, a TCBR System intended for storage and retrieval of Frequently Asked Questions (FAQs) named FAQCase was developed. Experiments were conducted to examine the effect of synonym-based query expansion on the system. The result has shown that there is significant retrieval improvement in FAQCase with query expansion over FAQCase without query expansion, in a situation where vocabulary mismatch between new questions and the stored FAQs is high.Keywords: Query expansion, Textual case-based reasoning, Word sense disambiguation, WordNetNigerian Journal of Basic and Applied Science (2011), 19 (2): 269-27