International Journal of Information Science and Management
Volume:14 Issue: 2, Jul-Dec 2016

This paper was aimed at clarifying the links between Uses and Gratification Theory (UGT) and Knowledge and Information Science in both traditional and modern contexts. Uses and Gratification conceptual model were also proposed both for library and information centers, and for interactive information retrieval systems. Review and analysis of published resources were used as the methodology of the article. Findings showed that UGT is in close connection with five laws of library science and their web version on one hand, and the user-oriented paradigm on the other hand. Therefore, the components of uses and gratification conceptual model of knowledge and information science in traditional and modern contexts consist of vast types of information needs, society, end user's features, information gratification sought, information gratification obtained, relevance gratification, library and information centers, and interactive information retrieval system uses. Applying UGT to knowledge and information science makes it possible to identify active and inactive users based on cognitive-cultural patterns. Moreover, automatic personalized interactive information retrieval systems were improved.

Provides an overview of Subject Repositories (SRs) throughout the World in response to the open access movement (OAM). It mainly highlights the current trends of repository development in Library and Information Science (LIS) field. This paper covers all repositories in LIS field as registered in OpenDOAR (Directory of Open Access Repository) database. The main objective of the paper is to select a set of parameters for evaluation of LIS repositories with other disciplinary repositories taking into consideration global recommendations and best practice guidelines. The paper also shows the growth of selected LIS repositories in terms of volume and number of objects, contents type, software pattern, subjects coverage etc. Lastly points out lacunas of LIS repositories in compare to other disciplinary repositories as well as recommends possible directions which can make the repository sustainable and will change the culture of information exchange pattern in the social science disciplines as a whole.

It has seen in many studies that there is a significant relation between the number of authors in an article and its amount of perceived citations. In other words, the more the number of the authors, the more the possibility of perceiving citations. The present study thus is going to explain a kind of behavior, which is based on Citing Conformity factor. The research has been done in two parts: 1. Survey Method 2. Citation analysis method. The findings obtained from regression analysis test suggest that according to Informational Citing Conformity factor, 26% of changes in this type of behavior are predictable. It means, having a motivation for healthy thoughts and honesty and also selecting more credible source of information, the authors resort to cite the articles which were written by more authors. The results also indicated that Normative Citing Conformity is not a suitable predictor for this kind of motivation. The relationship between Citing Conformity Factors (Normative, Informational) and the motivation to cite multi author articles has been analyzed in this research for the first time.

Success of an organization, more than anything else, depends on the human resources. Behavioral science emphasizes that organizational success mainly depends on efficient use of human resources. It is especially true in organizations such as libraries. To promote “positive thinking” ” among the staff of libraries and information centers, training courses should be arranged. To improve librarian's efficiency, these training courses should be held within the framework of an overall continuous program. In this research, the degree of “positive thinking” of librarians in 13 central university libraries affiliated to the Ministry of Science, Research and Technology (MSRT) in Tehran was assessed. Using random stratified sampling and random digits’ table, 144 employees were selected from among the total 218 employees working in these libraries as sample population. An author made checklist, which was based on Ingram and Wisnicki’s 5-factor questionnaire and consisted of 30 items, was applied as data-gathering tool. Descriptive survey was applied and the results showed the average values for positive daily functioning, positive self-evaluation, others evaluation of self, positive future expectations, and self-confidence were 3.737, 3.833, 3.965, 3.94, and 3,555 respectively. Among the five options of always, often, limited, sometimes and never, which are five options of Liker’s questionnaire, the tendency was toward choosing either often or always.

The main purpose of this paper is to study the IT-based job opportunities for Library and Information Science (LIS) graduates and identify the necessary competencies for an “IT librarian”. In a purposeful sampling, 596 advertisements of IT-based librarian jobs for LIS graduates in 10 countries on Indeed.com in 2013 were selected and analyzed. The findings showed that the four job categories, namely “IT Librarian”, “Digital Librarian/ Digital Services Librarian”, “Metadata Librarian”, and “Digital Archivist”, have 38% (227), 36% (213), 17% (103), and 9% (53) of the job advertisements respectively. Moreover, the findings revealed that 75 items of knowledge and skills are in the job advertisements of the "IT Librarian" job category. To the authors’ knowledge, the present research is the first to comprehensively identify newly emerging IT-based job titles in the field of Library and Information Science. It exhaustively reports the required competencies in the “IT Librarian” job category.

The relationship between transformational leadership behaviors and knowledge sharing in Alvan Sabet Company is highlighted in this study. According to leaders of Alvan Sabet Co. the target populations of the research are totally 47 persons. Census Method has been used in this research due to population size. One main hypothesis and four sub-hypotheses which have been obtained from reviewing the related literature in the field were dealt with in this study. The target population responded to the questionnaires being distributed among them, and the final results displayed a high correlation between the transformational leadership style and knowledge sharing (0.771).

A bilingual corpus is considered as a very important knowledge source and an inevitable requirement for many natural language processing (NLP) applications in which two languages are involved. For some languages such as Persian, lack of such resources is much more significant. Several applications, including statistical and example-based machine translation needs bilingual corpora, in which large amounts of texts from two different languages have been aligned at the sentence or phrase levels. In order to meet this requirement, this paper aims to propose an accurate and hybrid sentence alignment method for construction of an English-Persian parallel corpus. As the first step, the proposed method uses statistical length based analysis for filtering of candidates. Punctuation marks are used as a directing feature to reduce the complexity and increase the accuracy. Finally, the proposed method makes use of some lexical knowledge in order to produce the final output. . In the phase of lexical analysis, a bilingual dictionary as well as a Persian semantic net (denoted as FarsNet) is used to calculate the extended semantic similarity. Experiments showed the positive effect of expansion on synonym words by extended semantic similarity on the accuracy of the sentence alignment process. In the proposed matching scheme, a semantic load based approach (which considers the verb as the pivot and the main part of a sentence) was also used in order for increasing the accuracy. The results obtained from the experiments were promising and the generated parallel corpus can be used as an effective knowledge source by researchers who work on Persian language.

Stemming is the process of finding the main morpheme of a word and it is used in natural language processing, text mining and information retrieval systems. A stemmer extracts the stem of the words. Persian stemmers are classified into three main classes: structural stemmers, dictionary based stemmers, and statistical stemmers. The precision of structural stemmers is low and the expenses of dictionary based stemmers is high; therefore, the main goal of this research was to design and implement a statistical stemmer based on Hidden Markov Model with high precision in order to reduce the size of indexed file and increase the speed of information retrieval systems. In the present study, the proposed stemmer finds the prefixes and suffixes of a word and removes them, so that the rest of the word is considered to be the stem. But there are some exceptions in Persian words which would be considered as a stem mistakenly. So, at first a dictionary of Persian stemmers was collected and after that the proposed stemmer searched a word in the dictionary, if the word was not there, the stemmer found the stem of it by HMM based stemmer. This stemmer was tested in Bijankhan corpus and Hamshahri test collection. The results showed increment in mean average precision and recall. The speed of the Information retrieval system was increased and the size of indexed files were decreased by the algorithm.