Franck Ravat

Algebraic and Graphic Languages for OLAP Manipulations

This article deals with multidimensional analyses. Analyzed data are designed according to a conceptual model as a constellation of facts and dimensions, which are composed of multi-hierarchies. This model supports a query algebra defining a minimal core of operators, which produce multidimensional tables for displaying analyzed data. This user-oriented algebra supports complex analyses through advanced operators and binary operators. A graphical language, based on this algebra, is also provided to ease the specification of multidimensional queries. These graphical manipulations are expressed from a constellation schema and they produce multidimensional tables.

Preference-Based Recommendations for OLAP Analysis

This paper presents a framework for integrating OLAP and recommendations. We focus on the anticipatory recommendation process that assists the user during his OLAP analysis by proposing to him the forthcoming analysis step. We present a context-aware preference model that matches decision-makers intuition, and we discuss a preference-based approach for generating personalized recommendations.

Finding an application-appropriate model for XML data warehouses

Decision support systems help the decision making process with the use of OLAP (On-Line Analytical Processing) and data warehouses. These systems allow the analysis of corporate data. As OLAP and data warehousing evolve, more and more complex data is being used. XML (Extensible Markup Language) is a flexible text format allowing the interchange and the representation of complex data. Finding an appropriate model for an XML data warehouse tends to become complicated as more and more solutions appear. Hence, in this survey paper we present an overview of the different proposals that use XML within data warehousing technology. These proposals range from using XML data sources for regular warehouses to those using full XML warehousing solutions. Some researches merely focus on document storage facilities while others present adaptations of XML technology for OLAP. Even though there are a growing number of researches on the subject, many issues still remain unsolved.

Applying Recommendation Technology in OLAP Systems

OLAP systems offering multidimensional and large information space cannot solely rely on standard navigation but need to apply recommendations to make the analysis process easy and to help users quickly find relevant data for decision-making. In this paper, we propose a recommendation methodology for assisting the user during his decision-support analysis. The system helps the user in querying multidimensional data and exposes him to the most interesting patterns, i.e. it provides to the user anticipatory as well as alternative decision-support data. We provide a preference-based approach to apply such methodology.

Personalization and OLAP Databases

This paper focuses on the integration of personalization in a multidimensional context. We provide (i) a conceptual model, (ii) a query language and (iii) a personalized multidimensional database system. (i) The model we provide is based on multidimensional concepts (fact, dimension, hierarchy, measure, parameter or weak attribute) as well as personalization rules. These rules are based on Event-Condition-Action formalism and assign priority weights to attributes of a multidimensional schema. (ii) We also define OLAP operators adapted to the personalization context. Weights are taken into account during OLAP analyses; e.g. data with higher weights are displayed thus reducing the number of multidimensional operations a decision-maker executes during an analysis. (iii) This solution has been implemented in a prototype, which allows users both to define personalized rules and to query the personalized database. The system integrates user interfaces on top of an R-

Management of context-aware preferences in multidimensional databases

Personalization of information systems brings new challenges to OLAP technology. A key characteristic of emerging OLAP database systems will be customizability of their behaviour taking into account users preferences as well as their context of analysis. In this paper we define a personalization framework for OLAP database systems based on user context-aware preferences. We consider a qualitative preference model which handles user preferences on the multidimensional schema. Context is modelled as a tree of multidimensional components of an OLAP analysis (fact, measures, dimensions, parameters). We define some OLAP operations that support personalization. User queries are dynamically enhanced with his preferences and are aware of the analysis context.

Graphical querying of multidimensional databases

This paper provides an answer-oriented multidimensional analysis environment. The approach is based on a conceptual point of view. We define a conceptual model that represents data through a constellation of facts and dimensions and we present a query algebra handling multidimensional data as well as multidimensional tables. Based on these two propositions, in order to ease the specification of multidimensional analysis queries, we define a formal graphical language implemented within a prototype: GraphicOLAPSQL.

Top_Keyword: An Aggregation Function for Textual Document OLAP

For more than a decade, researches on OLAP and multidimensional databases have generated methodologies, tools and resource management systems for the analysis of numeric data. With the growing availability of digital documents, there is a need for incorporating text-rich documents within multidimensional databases as well as an adapted framework for their analysis. This paper presents a new aggregation function that aggregates textual data in an OLAP environment. The Top_Keyword function ( Top_Kw for short) represents a set of documents by their most significant terms using a weighing function from information retrieval: tf.idf.

A conceptual model for multidimensional analysis of documents

Data warehousing and OLAP are mainly used for the analysis of transactional data. Nowadays, with the evolution of Internet, and the development of semi-structured data exchange format (such as XML), it is possible to consider entire fragments of data such as documents as analysis sources. As a consequence, an adapted multidimensional analysis framework needs to be provided. In this paper, we introduce an OLAP multidimensional conceptual model without facts. This model is based on the unique concept of dimensions and is adapted for multidimensional document analysis. We also provide a set of manipulation operations.

A Temporal Object-Oriented Data Warehouse Model

The data warehousing approach intends to exploit a very large volume of data to make relevant decisions. In this paper, we deal with object-oriented data warehouse design. More precisely, we present an object-oriented data warehouse model, integrating temporal and archive data. We provide functions allowing the administrator to specify a data warehouse from a global source schema.