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A survey of the current state of documentation practice in museums is presented. This concentrates on the broad themes of the practice, making comparisons with analogous library procedures, where appropriate. A brief introduction to museums and their organizational framework within the United Kingdom is given. With this as background, the methods of documentation used by museums are reviewed, and a survey presented of current developments on an international and national scale.

There is a huge amount of information and data stored in publicly available online databases that consist of large text files accessed by Boolean search techniques. It is widely held that less use is made of these databases than could or should be the case, and that one reason for this is that potential users find it difficult to identify which databases to search, to use the various command languages of the hosts and to construct the Boolean search statements required. This reasoning has stimulated a considerable amount of exploration and development work on the construction of search interfaces, to aid the inexperienced user to gain effective access to these databases. The aim of our paper is to review aspects of the design of such interfaces: to indicate the requirements that must be met if maximum aid is to be offered to the inexperienced searcher; to spell out the knowledge that must be incorporated in an interface if such aid is to be given; to describe some of the solutions that have been implemented in experimental and operational interfaces; and to discuss some of the problems encountered. The paper closes with an extensive bibliography of references relevant to online search aids, going well beyond the items explicitly mentioned in the text. An index to software appears after the bibliography at the end of the paper.

To evaluate the accuracy of conflation methods based on finite‐state transducers (FSTs).

Incorrectly lemmatized and stemmed forms may lead to the retrieval of inappropriate documents. Experimental studies to date have focused on retrieval performance, but very few on conflation performance. The process of normalization we used involved a linguistic toolbox that allowed us to construct, through graphic interfaces, electronic dictionaries represented internally by FSTs. The lexical resources developed were applied to a Spanish test corpus for merging term variants in canonical lemmatized forms. Conflation performance was evaluated in terms of an adaptation of recall and precision measures, based on accuracy and coverage, not actual retrieval. The results were compared with those obtained using a Spanish version of the Porter algorithm.

The conclusion is that the main strength of lemmatization is its accuracy, whereas its main limitation is the underanalysis of variant forms.

The report outlines the potential of transducers in their application to normalization processes.

To propose a categorization of the different conflation procedures at the two basic approaches, non‐linguistic and linguistic techniques, and to justify the application of normalization methods within the framework of linguistic techniques.

Presents a range of term conflation methods, that can be used in information retrieval. The uniterm and multiterm variants can be considered equivalent units for the purposes of automatic indexing. Stemming algorithms, segmentation rules, association measures and clustering techniques are well evaluated non‐linguistic methods, and experiments with these techniques show a wide variety of results. Alternatively, the lemmatisation and the use of syntactic pattern‐matching, through equivalence relations represented in finite‐state transducers (FST), are emerging methods for the recognition and standardization of terms.

The survey attempts to point out the positive and negative effects of the linguistic approach and its potential as a term conflation method.

Outlines the importance of FSTs for the normalization of term variants.

In 1980, Porter presented a simple algorithm for stemming English language words. This paper summarises the main features of the algorithm, and highlights its role not just in modern information retrieval research, but also in a range of related subject domains.

Review of literature and research involving use of the Porter algorithm.

The algorithm has been widely adopted and extended so that it has become the standard approach to word conflation for information retrieval in a wide range of languages.

The 1980 paper in Program by Porter describing his algorithm has been highly cited. This paper provides a context for the original paper as well as an overview of its subsequent use.

This paper provides an introduction to the use of n‐grams in textual information systems, where an n‐gram is a string of n, usually adjacent, characters extracted from a section of continuous text. Applications that can be implemented efficiently and effectively using sets of n‐grams include spelling error detection and correction, query expansion, information retrieval with serial, inverted and signature files, dictionary look‐up, text compression, and language identification.

Einführung in das Portfolio‐Management Allgemein ist in den letzten 5–10 Jahren zunehmendes Interesse der Wirtschaft und Verwaltung für Probleme der strategischen Planung festzustellen, nicht zuletzt aufgrund der Diskussion über das Portfolio‐Management. Dieses neue Planungsmodell rückt durch die Definition sogenannter Strategischer Geschäftsfelder (“business units”, vgl. Abschnitt 2 dieses Aufsatzes) als strategische Planung aus gesamtunternehmerischer Sicht in den Mittelpunkt der Betrachtung und löst sich damit los von der engen Funktionalorientierung, bei der jeder strategische Bereich als eigene und relativ unabhängige Planungseinheit auftritt. Abell/Hammond sprechen in diesem Zusammenhang von einem 3‐zyklischen Planungsprozess (Abell/Hammond 1979, S. 14) (vgl. Abb. 1); die Längeund Breite der einzelnen Planungsstufen geben gleichzeitig ihre zeitliche Dauer und ihre relative Bedeutung wieder.

This paper reports on the successful introduction of a sophisticated online catalogue system at the library of the Scott Polar Research Institute, Cambridge, using the Muscat program package. The system provides to both end‐users and library staff a choice between boolean searching on keywords and access using relevance feedback based on free text in English, mixed with UDC classification numbers. The system is implemented on an IBM 3084 computer. Significant benefits from the application of relevance feedback are reported with 10,000 records on file.

Database management systems (DBMS) and information retrieval (IR) systems can both be used as online information systems but they differ in the type of data and the types of retrieval they provide for users. Many previous attempts have been made to couple DBMS and IR systems together, either by integrating the two into a unified framework, or by using a DBMS as an implementation tool for information retrieval functionality. This paper reports on some of these previous attempts and describes a system, retriev, which uses a DBMS to implement an IR system for teaching and research purposes. The implementation of retriev is described in detail and the effects that the current trends in database research will have on the relationship between DBMS and IR systems, are discussed.

Community detection is a significant research field in the study of social networks and analysis because of its tremendous applicability in multiple domains such as recommendation systems, link prediction and information diffusion. The majority of the present community detection methods considers either node information only or edge information only, but not both, which can result in loss of important information regarding network structures. In real-world social networks such as Facebook and Twitter, there are many heterogeneous aspects of the entities that connect them together such as different type of interactions occurring, which are difficult to study with the help of homogeneous network structures. The purpose of this study is to explore multilayer network design to capture these heterogeneous aspects by combining different modalities of interactions in single network.

In this work, multilayer network model is designed while taking into account node information as well as edge information. Existing community detection algorithms are applied on the designed multilayer network to find the densely connected nodes. Community scoring functions and partition comparison are used to further analyze the community structures. In addition to this, analytic hierarchical processing-technique for order preference by similarity to ideal solution (AHP-TOPSIS)-based framework is proposed for selection of an optimal community detection algorithm.

In the absence of reliable ground-truth communities, it becomes hard to perform evaluation of generated network communities. To overcome this problem, in this paper, various community scoring functions are computed and studied for different community detection methods.

In this study, evaluation criteria are considered to be independent. The authors observed that the criteria used are having some interdependencies, which could not be captured by the AHP method. Therefore, in future, analytic network process may be explored to capture these interdependencies among the decision attributes.

Proposed ranking can be used to improve the search strategy of algorithms to decrease the search time of the best fitting one according to the case study. The suggested study ranks existing community detection algorithms to find the most appropriate one.

Community detection is useful in many applications such as recommendation systems, health care, politics, economics, e-commerce, social media and communication network.

Ranking of the community detection algorithms is performed using community scoring functions as well as AHP-TOPSIS methods.