Abstract. Research on multimedia information retrieval (MIR) has recently witnessed a booming interest. A prominent feature of this research trend is its simultaneous but independent materialization within several fields of computer science. The resulting richness of paradigms, methods and systems may, on the long run, result in a fragmentation of efforts and slow down progress. The primary goal of this study is to promote an integration of methods and techniques for MIR by contributing a conceptual model that encompasses in a unified and coherent perspective the many efforts that are being produced under the label of MIR. The model offers a retrieval capability that spans two media, text and images, but also several dimensions: form, content and structure. In this way, it reconciles similarity-based methods with semantics-based ones, providing the guidelines for the design of systems that are able to provide a generalized multimedia retrieval service, in which the existing forms of retrieval not only coexist, but can be combined in any desired manner. The model is formulated in terms of a fuzzy description logic, which plays a twofold role: (1) it directly models semantics-based retrieval, and (2) it offers an ideal framework for the integration of the multimedia and multidimensional aspects of retrieval mentioned above. The model also accounts for relevance feedback in both text and image retrieval, integrating known techniques for taking into account user judgments. The implementation of

Documents often display a structure determined by the author, e.g., several chapters, each with several sub-chapters and so on. Taking into account the structure of a document allows the retrieval process to focus on those parts of the documents that are most relevant to an information need. Chiaramella et al advanced a model for indexing and retrieving structured documents. Their aim was to express the model within a framework based on formal logics with associated theories. They developed the logical formalism of the model. This paper adds to this model a theory of uncertainty, the Dempster-Shafer theory of evidence. It is shown that the theory provides a rule, the Dempster's combination rule, that allows the expression of the uncertainty with respect to parts of a document, and that is compatible with the logical model developed by Chiaramella et al.

: A core concept in discussions about technological support for knowledge management is the Corporate Memory. A Corporate or Organizational Memory can be characterized as a comprehensive computer system which captures a company's accumulated know-how and other knowledge assets and makes them available to enhance the efficiency and effectiveness of knowledge-intensive work processes. The successful development of such a system requires a careful analysis of established work practices and available information-technology (IT) infrastructure. This is essential for providing a cost-effective solution which will be accepted by the users and can be evolved in the future. The current paper compares and summarizes our experiences from three case studies on Corporate Memories for supporting various aspects in the product life-cycles of three European corporations. Based on the conducted analyses and prototypical implementations, we sketch a general framework for the development methodology, arc...

. HySpirit is a retrieval engine for hypermedia retrieval integrating concepts from information retrieval (IR) and deductive databases. The logical view on IR models retrieval as uncertain inference, for which we use probabilistic reasoning. Since the expressiveness of classical IR models is not sufficient for hypermedia retrieval, HySpirit is based on a probabilistic version of Datalog. In hypermedia retrieval, different nodes may contain contradictory information; thus, we introduce probabilistic four-valued Datalog. In order to support fact queries as well as contentbased retrieval, HySpirit is based on an open world assumption, but allows for predicate-specific closed world assumptions. For performing efficient retrieval on large databases, our system provides access to external data. We demonstrate the application of HySpirit by giving examples for retrieval on images, structured documents and large databases. 1 Introduction Due to the advances in hardware, processing of multimed...

Semantic Portal is the next generation of web portals that are powered by Semantic Web technologies for improved information sharing and exchange for a community of users. Current methods of searching in Semantic Portals are limited to keyword-based search using information retrieval (IR) techniques, ontology-based formal query and reasoning, or a simple combination of the two. In this paper, we propose an enhanced model that tightly integrates IR with formal query and reasoning to fully utilize both textual and semantic information for searching in Semantic Portals. The model extends the search capabilities of existing methods and can answer more complex search requests. The ideas in a fuzzy description logic (DL) IR model and a formal DL query method are employed and combined in our model. Based on the model, a semantic search service is implemented and evaluated. The evaluation shows very large improvements over existing methods.

Information Retrieval (IR) is concerned with locating documents that are relevant for a user's information need or query from a large collection of documents. A fundamental problem for information retrieval is word mismatch. A query is usually a short and incomplete description of the underlying information need. The users of IR systems and the authors of the documents often use different words to refer to the same concepts. This thesis addresses the word mismatch problem through automatic text analysis. We investigate two text analysis techniques, corpus analysis and local context analysis, and apply them in two domains of word mismatch, stemming and general query expansion. Experimental results show that these techniques ca...

Description Logics (DLs, for short) provide a logical reconstruction of the so-called frame-based knowledge representation languages. Originally, four-valued DLs have been proposed in order to develop expressively powerful DLs with tractable subsumption algorithms. Recently, four-valued DLs have been proposed as a model for (multimedia) document retrieval. In this context, the main reasoning task is instance checking. Unfortunately, the known subsumption algorithms for four-valued DLs, based on "structural" subsumption, do not work with respect to the semantics proposed in the DL-based approach to document retrieval. Moreover, they are unsuitable for solving the instance checking problem, as this latter problem is more general than the subsumption problem. We present an alternative decision procedure for four-valued DLs with the aim to solve these problems. The decision procedure is a sequent calculus for instance checking. Since in general the four-valued subsumption problem can be ...

Abstract. We present a model for complex documents possibly consisting of a hierarchically structured set of images or texts. Documents are represented both at the form level (as sets of physical features of the representing objects), at the content level (as sets of properties of the represented entities), and at the structure level. A uniform and powerful query language allows queries to be issued that transparently combine features pertaining to form, content and structure alike. Queries are expressions of a (fuzzy) logical language. While that part of the query that pertains to (medium-independent) content is “directly ” processed by an inferential engine, that part that pertains to (medium-dependent) form is entrusted to specialised document processing procedures linked to the logical language by a procedural attachment mechanism. The model thus combines the power of state-of-the-art document processing techniques with the advantages of a clean, logically defined framework for understanding multimedia document retrieval. 1

. Knowledge representation, in particular logic, combined together with database and information retrieval techniques may play an important role in the development of so-called intelligent multimedia retrieval systems. In this paper we will present a logic-based framework in which multimedia objects' medium dependent properties (objects' low level features) and multimedia objects' medium independent properties (abstract objects' features, or objects' semantics) are addressed in a principled way. The framework is logic-based as it relies on the use of a four-valued fuzzy Description Logics for (i) representing the semantics of multimedia objects and (ii) for defining the retrieval process in terms of logical entailment. Low level features are not represented explicitly within the logic, but may be addressed by means of procedural attachments over a concrete domain. Description Logics are object-oriented representation formalisms capturing the most popular features of structured represen...

We present a model for image retrieval in which images are represented both at the form level, as sets of physical features of the representing objects, and at the content level, as sets of logical assertions about the represented entities as well as about facts of the subject matter that are deemed as relevant for retrieval. A uniform and powerful query language allows queries to be issued that transparently combine features pertaining to form and content. Queries are expressions of a fuzzy logical language. While that part of the query that pertains to (medium-independent) content is "directly" processed by an inferential engine, that part that pertains to (medium-dependent) form is entrusted to specialised signal processing procedures linked to the logical language by a procedural attachment mechanism.