Timo Niemi

ExpansionTool: Concept-Based Query Expansion and Construction

We develop a deductive data model for concept-based query expansion. It is based on three abstraction levels: the conceptual, linguistic and string levels. Concepts and relationships among them are represented at the conceptual level. The linguistic level gives natural language expressions for concepts. Each expression has one or more matching patterns at the string level. The models specify the matching of the expression in database indices built in varying ways. The data model supports a declarative concept-based query expansion and formulation tool, the ExpansionTool, for heterogeneous IR system environments. Conceptual expansion is implemented by a novel intelligent operator for traversing transitive relationships among cyclic concept networks. The number of expansion links followed, their types, and weights can be used to control expansion. A sample empirical experiment illustrating the use of the ExpansionTool in IR experiments is presented.

A deductive data model for query expansion

We present a deductive data model for concept-based query expansion. It is based on three abstraction levels: the conceptual, the expression and the occurrence level. Concepts and their relationships are represented at the conceptual level. The expression level represents natural language expressions for concepts. Each expression has one or more matching models at the occurrence level. Each model specifies the matching of the expression in database indices built in varying ways. The data model supports a concept-based query expantion and formulation tool, the ExpansionTool, for environments providing heterogeneous IR systems. Expansion is controlled by adjustable matching reliability. Published in: H.-;P. Frei, D. Harman, P. Schauble, and R. Wilkinson (eds.) Proceedings of the 19th Annual International ACM‹SIGIR Conference on Research and Development in Information Retrieval, Zurich, August 18.-22.1996, pp. 235-249. ____________________ The INQUERY retrieval system was used in part of this research. The INQUERY software was provided by the Information Retrieval Laboratory, University of Massachusetts Computer Science Department, Amherst, MA, USA. 1 ______________________________________________________________________________________________ ______________________________________________________________________________________________ A Deductive Data Model for Query Expansion

A seven-tuple representation for hierarchical data structures

Abstract Different kinds of data structure diagrams, especially Bachmans, and tabular representations are very often used to visualize hierarchical data structures. The popularity of these visual modes of representation is due to the possibility they afford of describing data structures clearly and regardless of any implementation. However, it has been observed in diverse contexts that instead of the visualization we need a general and exact representation containing the same structural components as these visual representations. In this paper we introduce a seven-tuple representation which can be used for exact description of any hierarchical data structure. We give both the explicit construction operations and the implicit rules which can be utilized in forming any hierarchical data structure. We show that the formal representation introduced contains the descriptive power of the visualization methods mentioned above. Furthermore we examine how, in the context of this representation, it is possible to define flexibly general analyzing functions for hierarchical data structures.

Prolog-based meta-rules for relational database representation and manipulation

A Prolog-based experimental system for relational databases that is not defined from the viewpoint of any specific relational topic is proposed. The idea is that the experimental system can be used in many different contexts such as query optimization, data restructuring and database design. The definition is based entirely on the theoretical foundations of the relational model. The experimental system offers a well-defined environment for studying how other systems can be integrated with relational databases. The use of the experimental system in the context of different approaches to deductive databases is considered. >

A relational data harmonization approach to XML

There are numerous approaches for integrating data from heterogeneous data sources. A common background assumption is that the data sources remain quite stable and are known in advance. Hence an integration system can be built to manipulate them. In practice there is, however, often a demand for supporting ad hoc information needs concerning unexpected autonomous data sources containing volatile data. A different approach is therefore needed. We propose that semantically similar data are harmonized when extracting data from XML-based data sources. We introduce a constructor algebra, which is a powerful tool in the harmonization of XML data. This algebra is able to form for any XML data source a unique relational representation, called an XML relation. We demonstrate that the XML relation representation supports grouping and aggregation of data needed, for example, in OLAP (online analytical processing) -style applications.

A straightforward NF 2 relational interface with applications in information retrieval

Abstract In information retrieval (IR) there is a need for greater structural expressiveness than that provided by ordinary retrieval systems or the ordinary relational model. Especially hierarchical structures are usual in IR applications. Therefore the non-first-normal-form (NF2) relational model often is a more natural and intuitive way to model data of IR applications than the pure relational model. Because many-to-many relationships often exist among real world entities of IR applications, it is impossible to find a stable hierarchical structure suitable to all needs of users. This means that a tool is needed that has a powerful restructuring capability. In other words, it has to be able to produce for the user result NF2 relations in which hierarchical relationships among data have been organized in a way that is drastically different from that in the source NF2 relations. In this paper we classify typical data restructuring tasks in an IR environment, and give several examples on their specifications. It has been widely recognized that NF2 relational query formulation with conventional query languages is too cumbersome for ordinary end users. In order to simplify NF2 relational query formulation, we have developed and implemented a novel user interface. We show that query specification in this interface remains compact and truly declarative—also in the context of complex NF2 relational queries.

A User-Oriented Interface for Generalised Informetric Analysis Based on Applying Advanced Data Modelling Techniques.

This article presents a novel user‐oriented interface for generalised informetric analysis and demonstrates how informetric calculations can easily and declaratively be specified through advanced data modelling techniques. The interface is declarative and at a high level. Therefore it is easy to use, flexible and extensible. It enables end users to perform basic informetric ad hoc calculations easily and often with much less effort than in contemporary online retrieval systems. It also provides several fruitful generalisations of typical informetric measurements like impact factors. These are based on substituting traditional foci of analysis, for instance journals, by other object types, such as authors, organisations or countries. In the interface, bibliographic data are modelled as complex objects (non‐first normal form relations) and terminological and citation networks involving transitive relationships are modelled as binary relations for deductive processing. The interface is flexible, because it m...

Operation-oriented query language approach for recursive queries—part 1.: functional definition

Abstract So far the aspects related to efficient processing have dominated the research on recursive queries. In this paper we consider how the formulation of recursive queries can be made easier from the view point of the non-professional user—also in the context of complex recursive queries. It is obvious that the conventional rule-based way of defining is too hard and cumbersome for many non-professional users. We provide operations at a high abstraction level in terms which the user can formulate his recursive queries in a compact and convenient way. In our approach recursive processing is needed for constructing transitive relationships among data. In practice, it is often very important to compute transitive relationships among several union-compatible binary relations instead of one binary relation as usual. We define the operations so that they are able to manipulate transitive relationships among several relations. For the changing needs of the user our approach contains three kinds of operations: relation-oriented, node-oriented and path-oriented operations. In this paper we specify a functional language consisting of operations of these types and give several examples on how the user can formulate his recursive queries in terms of this language. We also discuss its role in deductive databases, i.e. its integration with processing based on an extensional database.

A straightforward formalization of the relational model

Abstract There has been a lot of recent interest in the formalization of the relational data model (RDM). Many approaches may be characterized as ones oriented mainly towards declaring the components of the RDM and their interrelationships. Other approaches provide also a tool for manipulating the components of RDM so that research topics on the model can be specified exactly. Usually the latter approaches are based on formal specification methods such as denotational semantics or abstract data types. However some in the data base community find them quite complex and cumbersome. The goal of the approach of this paper is of the latter kind. However, special attention is being paid to avoid the complexity of the formal specification methods because our notations and definitions are based on set theory. We attempt to provide an exact, convenient and general tool for specifications and proofs concerning various topics like relational query languages, query optimization, relational data base restructuring, data base design, etc.

Query language approach based on the deductive object-oriented database paradigm

Abstract The integration of data-oriented (structural), behavioral and deductive aspects is necessary in next generation information systems. The deductive object-oriented database paradigm offers a very promising starting point for the implementation of these kinds of information systems. So far in the context of this paradigm a big problem has been the lack of a query language suitable to an ordinary end user. Typically in existing proposals for deductive object-oriented databases the user has to master well both logic-based rule formulation and object-oriented programming. In this paper we introduce a set of high-level querying primitives which increases the degree of declarativeness compared to the deductive object-oriented query languages proposed so far. In terms of these primitives it is possible to offer for end users such application-specific concepts and structures whose interpretation is obvious to users but whose specification is too demanding for them. By combining these primitives in queries the user can integrate data-oriented, behavioral and deductive aspects with each other in a concept-oriented way. Our query language approach is based on the incorporation of deductive aspects to object-orientation. Among others this means that deductive aspects of objects are inherited in the specialization/generalization hierarchy like any other properties of objects.