Challenging Ubiquitous Inverted Files

Stand-alone ranking systems based on highly optimized inverted file structures are generally considered ‘the’ solution for building search engines. Observing various developments in software and hardware, we argue however that IR research faces a complex engineering problem in the quest for more flexible yet efficient retrieval systems. We propose to base the development of retrieval systems on ‘the database approach’: mapping high-level declarative specifications of the retrieval process into efficient query plans. We present the Mirror DBMS as a prototype implementation of a retrieval system based on this approach

Visual intelligence for online communities : commonsense image retrieval by query expansion

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2004.Includes bibliographical references (leaves 65-67).This thesis explores three weaknesses of keyword-based image retrieval through the design and implementation of an actual image retrieval system. The first weakness is the requirement of heavy manual annotation of keywords for images. We investigate this weakness by aggregating the annotations of an entire community of users to alleviate the annotation requirements on the individual user. The second weakness is the hit-or-miss nature of exact keyword matching used in many existing image retrieval systems. We explore this weakness by using linguistics tools (WordNet and the OpenMind Commonsense database) to locate image keywords in a semantic network of interrelated concepts so that retrieval by keywords is automatically expanded semantically to avoid the hit-or-miss problem. Such semantic query expansion further alleviates the requirement for exhaustive manual annotation. The third weakness of keyword-based image retrieval systems is the lack of support for retrieval by subjective content. We investigate this weakness by creating a mechanism to allow users to annotate images by their subjective emotional content and subsequently to retrieve images by these emotions. This thesis is primarily an exploration of different keyword-based image retrieval techniques in a real image retrieval system. The design of the system is grounded in past research that sheds light onto how people actually encounter the task of describing images with words for future retrieval. The image retrieval system's front-end and back- end are fully integrated with the Treehouse Global Studio online community - an online environment with a suite of media design tools and database storage of media files and metadata.(cont.) The focus of the thesis is on exploring new user scenarios for keyword-based image retrieval rather than quantitative assessment of retrieval effectiveness. Traditional information retrieval evaluation metrics are discussed but not pursued. The user scenarios for our image retrieval system are analyzed qualitatively in terms of system design and how they facilitate the overall retrieval experience.James Jian Dai.S.M

The psychology of multimedia databases

Multimedia information retrieval in digital libraries is a difficult task for computers in general. Humans on the other hand are experts in perception, concept representation, knowledge organization and memory retrieval. Cognitive psychology and science describe how cognition works in humans, but can offer valuable clues to information retrieval researchers as well. Cognitive psychologists view the human mind as a general-purpose symbol-processing system that interacts with the world. A multimedia information retrieval system can also be regarded as a symbol-processing system that interacts with the environment. Its underlying information retrieval model can be seen as a cognitive framework that describes how the various aspects of cognition are related to each other. In this paper we describe the design and implementation of a combined text/image retrieval system (as an example of a multimedia retrieval system) that is inspired by cognitive theories such as Paivio's dual coding theory and Marr's theory of perception. User interaction and an automatically created thesaurus that maps text concepts and internal image concept representations, generated by various feature extraction algorithms, improve the query formulation process of the image retrieval system. Unlike most "multimedia databases" found in literature, this image retrieval system uses the the functionality provided by an extensible multimedia DBMS that itself is part of an open distributed environment

The psychology of multimedia databases

Multimedia information retrieval in digital libraries is a difficult task for computers in general. Humans on the other hand are experts in perception, concept representation, knowledge organization and memory retrieval. Cognitive psychology and science describe how cognition works in humans, but can offer valuable clues to information retrieval researchers as well. Cognitive psychologists view the human mind as a general-purpose symbol-processing system that interacts with the world. A multimedia information retrieval system can also be regarded as a symbol-processing system that interacts with the environment. Its underlying information retrieval model can be seen as a cognitive framework that describes how the various aspects of cognition are related to each other. In this paper we describe the design and implementation of a combined text/image retrieval system (as an example of a multimedia retrieval system) that is inspired by cognitive theories such as Paivio's dual coding theory and Marr's theory of perception. User interaction and an automatically created thesaurus that maps text concepts and internal image concept representations, generated by various feature extraction algorithms, improve the query formulation process of the image retrieval system. Unlike most "multimedia databases" found in literature, this image retrieval system uses the the functionality provided by an extensible multimedia DBMS that itself is part of an open distributed environment