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The purpose of this paper is to provide a detailed discussion for different types of graph queries and a different mechanism for indexing and querying graph databases.

The paper reviews the existing approaches and techniques for indexing and querying graph databases. For each approach, the strengths and weaknesses are discussed with particular emphasis on the target application domain. Based on an analysis of the state‐of‐the‐art of research literature, the paper provides insights for future research directions and untouched challenging research aspects.

Several graph indexing and querying techniques have been proposed in the literature. However, there is still a clear room for improvement and further research issues in that domain.

The paper identifies the advantages and disadvantages of the different graph indexing mechanisms and their suitability for different practical applications. The paper provides some guidelines and recommendations which are useful for future research in the area of graph databases.

The paper has practical implications for social networks, protein networks, chemical compounds, multimedia database, and semantic web.

The paper contributes to the implementation of an efficient indexing and querying mechanism for graph databases in different application domains.

The purpose of this paper is to propose a new model to enhance auto-indexing Arabic texts. The model denotes extracting new relevant words by relating those chosen by previous classical methods to new words using data mining rules.

The proposed model uses an association rule algorithm for extracting frequent sets containing related items – to extract relationships between words in the texts to be indexed with words from texts that belong to the same category. The associations of words extracted are illustrated as sets of words that appear frequently together.

The proposed methodology shows significant enhancement in terms of accuracy, efficiency and reliability when compared to previous works.

The stemming algorithm can be further enhanced. In the Arabic language, we have many grammatical rules. The more we integrate rules to the stemming algorithm, the better the stemming will be. Other enhancements can be done to the stop-list. This is by adding more words to it that should not be taken into consideration in the indexing mechanism. Also, numbers should be added to the list as well as using the thesaurus system because it links different phrases or words with the same meaning to each other, which improves the indexing mechanism. The authors also invite researchers to add more pre-requisite texts to have better results.

In this paper, the authors present a full text-based auto-indexing method for Arabic text documents. The auto-indexing method extracts new relevant words by using data mining rules, which has not been investigated before. The method uses an association rule mining algorithm for extracting frequent sets containing related items to extract relationships between words in the texts to be indexed with words from texts that belong to the same category. The benefits of the method are demonstrated using empirical work involving several Arabic texts.

Farradane's system of relational indexing, which had been previously used in a retrospective search system with good results, was further tested as the indexing language for an experimental S.D.I. system. Sections of Metals Abstracts were used for the data base of 2,820 abstracts, and forty‐three volunteer users participated in the experiment which lasted for six months. Performance was assessed by recall, precision and fallout ratios, and the ‘coefficient of association’ (Q value) and the product (recall X precision) were used as overall measures. The overall average performance was about 75% recall and 75% precision. A failure analysis was also carried out. The browsing strategies incorporated into the system were analysed, as were the profile structure, the distribution of performance measures and possible relationships between recall, precision and generality. Farradane's relational indexing appeared applicable to the different scientific area of the properties of metals and again gave good results with a greater depth of indexing. Some new features of the system were observed.

The paper describes research designed to improve automatic pre‐coordinate term indexing by applying powerful general‐purpose language analysis techniques to identify term sources in requests, and to generate variant expressions of the concepts involved for document text searching.

Reports a laboratory comparison of the effectiveness and efficiency of five index languages in the subject area of library and information science; three post‐co‐ordinate languages, Compressed Term, Uncontrolled, and Hierarchically Structured, and two pre‐co‐ordinate ones, Hierarchically Structured and Relational Indexing. Eight test comparisons were made, and factors studied were index language specificity and linkage, indexing specificity and exhaustivity, method of co‐ordination, the precision devices of partitioning and relational operators, and the provision of context in the search file. Full details of the test and retrieval results are presented.

For the last ten years or so there has been a flood of papers, books, lectures, symposia, and discussions on indexing, classification, mechanical selection, subject analysis, information retrieval, and so on. An earlier generation used words and subject headings: today we use isolates and analets, facets and phases, descriptors and uniterms. A ‘glossary of current terminology’ in classification now runs to 350 terms, mostly of recent coinage.

The indexes to The Times of London are unique in providing access to an unbroken record of events as recorded by one of the world's most prestigious newspapers over a period of two hundred years. They are, therefore, an important tool for the researcher, yet there has been little comment on their quality. This study provides an introductory comparative analysis of the two main indexes: Palmer's Index to the Times Newspaper and The Times Index. The two are evaluated according to selected criteria of good indexing such as consistency, concept versus keyword approach, and the use of subject headings and cross references. Samples from both the newspaper and the indexes have been taken over fifty‐year intervals to determine whether there have been any changes in indexing techniques over time. The findings reveal the superior qualities of The Times Index and outline the problems that the researcher may encounter in using Palmer's.

The indexing techniques most commonly applied in information retrieval systems associate weights to the terms of documents; this association is carried out in order to quantify the term’s capacity for representing the document. Subsequently, these weights are used in query processing, playing an important role in the performance of the system. This work presents a method for the adjustment of index weights by processing text that has been highlighted by users. Text in a document is highlighted using an application which provides annotation facilities in order to support active reading. Highlighted text is supposed to be of special relevance and the method tries to improve the index weights of terms located in these highlighted fragments.

The mini‐micro version of CDS/ISIS (Computerised Documentation System/ Integrated Set of Information Systems) is a generalised system developed by UNESCO for non‐numerical databases. The first version was released in 1985. The latest version, released in 1989, is version 2.3. It has many improvements over version 1; the most prominent ones being speedier file inversion (creation of indexes), a new facility of free‐text searching, a more versatile formatting language, and the PASCAL language module for programming.

To provide a better‐informed view of the extent of the semantic gap in image retrieval, and the limited potential for bridging it offered by current semantic image retrieval techniques.

Within an ongoing project, a broad spectrum of operational image retrieval activity has been surveyed, and, from a number of collaborating institutions, a test collection assembled which comprises user requests, the images selected in response to those requests, and their associated metadata. This has provided the evidence base upon which to make informed observations on the efficacy of cutting‐edge automatic annotation techniques which seek to integrate the text‐based and content‐based image retrieval paradigms.

Evidence from the real‐world practice of image retrieval highlights the existence of a generic‐specific continuum of object identification, and the incidence of temporal, spatial, significance and abstract concept facets, manifest in textual indexing and real‐query scenarios but often having no directly visible presence in an image. These factors combine to limit the functionality of current semantic image retrieval techniques, which interpret only visible features at the generic extremity of the generic‐specific continuum.

The project is concerned with the traditional image retrieval environment in which retrieval transactions are conducted on still images which form part of managed collections. The possibilities offered by ontological support for adding functionality to automatic annotation techniques are considered.

The paper offers fresh insights into the challenge of migrating content‐based image retrieval from the laboratory to the operational environment, informed by newly‐assembled, comprehensive, live data.