Automatic information retrieval is based on the assumption that texts contain content or structural elements that can be used in word sense disambiguation and thereby improving the effectiveness of the results retrieved. Homographs are among the words requiring sense disambiguation. Depending on their roles and positions in texts, homograph contexts could be divided to different types, with probably different potency in determination of similarity of documents. Using a content analysis method, the present research aims to compare the powers of five kinds of contexts including text citations, references, reference titles, paper titles and texts in homograph sense disambiguation. Applying a content analysis method, the present paper concentrates on a document test collection built on English homographs by choosing a sample consisted of 3637 articles containing 19 homographs about 54 subjects published during 2000-2015. Discriminant analysis was used to determine the similarity within or differentiation between the 54 document clusters. According to the results of the discriminant analyses carried out within each of the clusters, sub-clusters of documents can be observed, though with a very little differentiation in terms of the homograph contexts. Textcitation and reference contexts are revealed to have minimum role in differentiating between the documents within the clusters. Documents containing synonymous homographs form clusters within which documents are rather similar in terms of their homograph contexts. Furthermore, homograph context types are not equ al in their power to determine similarities. Text-citation context and reference context types showed the highest degree of similarities within the clusters. These two context types, which show high similarity within clusters, can be used to improve retrieval results. It is suggested that the results of the comparison of these two contexts can be used as a tool for secondary ranking or clustering of information retrieval results. This is the first research of its kind to define different text contexts and compare them in terms of their power to determine similarity of texts containing synonymous homographs.

In philosophical literature it has been enumerated different types of explanation such as scientific and ordinary, full and partial, causal and non-causal, functional explanations. By distinguishing these different explanations from each other, this paper provides an introduction to the discussion of theories of scientific explanation. The standard view about the nature of scientific explanation is the covering law model of explanation which is further divided into two sorts: deductive - nomological and inductive - probabilistic or statistical explanation. Difficulties faced by the covering model gave way to alternative models. And various alternative views about explanation have been developed, among them it can be cited Salmon's statistical relevance model which based on causal mechanism and Friedman and Kitcher's explanatory unification. This paper shows how later models avoid difficulties of earlier ones.

Scientific document centers are management centers for science and technology information. So, they could be considered as important mediators institutions of science and technology system in Iran. In order to investigate how these centers support institutions of science and technology policy and to ensure that there exist the relationships among these institutions, a framework is required to fill the existing gaps and find solutions for improving management and analyzing information for science and technology policy. According this, a model has been developed by mixed method in this study. Then, this model has been implemented in Iranian Research Institute for Information Science and Technology (IRANDOC).Using this model, the situation of IRANDOC support of science and technology policy has been evaluated from the perspective of policy-makers and administrators and experts of IRANDOC. The results of the study show the current situation of IRANDOC support is not appropriate. Some of the activities that IRANDOC and other scientific document centers can do in support of policy-making included: Access to the infrastructure in the organization to create the knowledge and analytical information required by science and technology policy-makers; Strengthen and improve the processes of diffusion of knowledge and information required by science and technology policy-makers; Access to the infrastructure in the organization to achieve the satisfactory cooperation in science and technology policy-making; Access to the infrastructure in the organization to help to complete and strengthen the infrastructure, rules and regulations of Science and Technology; Illustrate the position of IRANDOC brand among the institutions of science and technology policy; Access to the infrastructure in the organization to set up and organize statistics systems, for scientific, research and technology information.