Sharif Digital Repository

Taxonomy learning is one of the major steps in ontology learning process. Manual construction of taxonomies is a time-consuming and cumbersome task. Recently many researchers have focused on automatic taxonomy learning, but still quality of generated taxonomies is not satisfactory. In this paper we have proposed a new compound similarity measure. This measure is based on both knowledge poor and knowledge rich approaches to find word similarity. We also used Neural Network model for combination of several similarity methods. We have compared our method with simple syntactic similarity measure. Our measure considerably improves the precision and recall of automatic generated taxonomies. ©... 

In this paper, we propose an optimization framework to retrieve an optimal group of experts to perform a multi-aspect task. While a diverse set of skills are needed to perform a multi-aspect task, the group of assigned experts should be able to collectively cover all these required skills. We consider three types of multi-aspect expert group formation problems and propose a unified framework to solve these problems accurately and efficiently. The first problem is concerned with finding the top k experts for a given task, while the required skills of the task are implicitly described. In the second problem, the required skills of the tasks are explicitly described using some keywords but each... 

In this paper, we propose an optimization framework to retrieve an optimal group of experts to perform a given multi-aspect task/project. Each task needs a diverse set of skills and the group of assigned experts should be able to collectively cover all required aspects of the task. We consider three types of multiaspect team formation problems and propose a unified framework to solve these problems accurately and efficiently. Our proposed framework is based on Facility Location Analysis (FLA) which is a well known branch of the Operation Research (OR). Our experiments on a real dataset show significant improvement in comparison with the state-of-the art approaches for the team formation... 

Community Question Answering is one of the valuable information resources which provide users with a platform to share their knowledge. Finding potential experts in CQA is beneficial to several problems like low participation rate of the users, long waiting time to receive answers and to the low quality of answers. Many research papers focused on retrieving the expert users of CQAs. Most of them are taking expertise into consideration at the query time and ignore the temporal aspects of the expert finding problem. However, considering the evolution of personal expertise over time can improve the quality of expert finding. In many applications, it is beneficial to find the potential experts... 

Taxonomy learning is a prerequisite step for ontology learning. In order to create a taxonomy, first of all, existing 'is-a' relations between words should be extracted. A known way to extract 'is-a' relations is finding lexicosyntactic patterns in large text corpus. Although this approach produces results with high precision but it suffers from low values of recall. Furthermore developing a comprehensive set of patterns is tedious and cumbersome. In this paper, firstly, we introduce an approach for developing lexico-syntactic patterns automatically using the snippets of search engine results and then, challenge the law recall of this approach using a combined model, which is based on... 

Expert finding problem in bibliographic networks has received increased interest in recent years. This problem concerns finding relevant researchers for a given topic. Motivated by the observation that rarely do all coauthors contribute to a paper equally, in this paper, we propose two discriminative methods for realizing leading authors contributing in a scientific publication. Specifically, we cast the problem of expert finding in a bibliographic network to find leading experts in a research group, which is easier to solve. We recognize three feature groups that can discriminate relevant experts from other authors of a document. Experimental results on a real dataset, and a synthetic one... 

In this study, the anticorrosive effect of dodecylbenzenesulfonicacid-doped polyaniline nanoparticles [n-PANI (DBSA)] as a conductive polymer was investigated using electrochemical impedance spectroscopy (EIS) and X-ray photoelectron spectroscopy (XPS) techniques. Initially, the n-PANI (DBSA) were successfully synthesized via inverse microemulsion polymerization leading to the spherical nanoparticles with an average diameter less than 30 nm. Two coating systems including 1 wt% n-PANI(DBSA) blended epoxy ester (n-PANI(DBSA)/EPE) and neat epoxy ester (EPE) were coated on the carbon steal substrate. The anticorrosion performance of the prepared coatings was studied using EIS measurement in 3.5%... 

In this paper, we address the problem of scientific-social network integration to find a matching relationship between members of these networks. Utilizing several name similarity patterns and contextual properties of these networks, we design a focused crawler to find high probable matching pairs, then the problem of name disambiguation is reduced to predict the label of each candidate pair as either true or false matching. By defining matching dependency graph, we propose a joint label prediction model to determine the label of all candidate pairs simultaneously. An extensive set of experiments have been conducted on six test collections obtained from the DBLP and the Twitter networks to... 

Measuring semantic similarity of web services has several benefits and most of the proposed service discovery algorithms are based on measuring the similarity of the requested service with each of the advertised services. In this paper, we propose a method for measuring the similarity of web services which are annotated with OWL-S ontology. First, a semantic similarity measure for determining the similarity of OWL concepts is discussed and then based on this measure, the functional similarity of services is defined. Then it is showed that the precision of algorithms that only take into account the functional properties of services for measuring their similarity are low. Therefore the textual... 

In this paper a closed-form expression is introduced to calculate slot shape of long slot leaky wave waveguide antennas at its fundamental mode of operation with minimum side lobe level (SLL). The derived equation is a function of geometrical parameters of the structure. This is an advantage because they show a clear relationship between geometrical parameters of the antenna and radiated field that allows intelligent modification of the pattern. The Gaussian slot is used to obtain the best radiation pattern with lowest SLL. The results obtained by introduced formula are compared with the full wave commercial simulator such as HFSS software which confirms the accuracy of the introduced... 

Taxonomy learning is one of the major steps in ontology learning process. Manual construction of taxonomies is a time-consuming and cumbersome task. Recently many researchers have focused on automatic taxonomy learning, but still quality of generated taxonomies is not satisfactory. In this paper we have proposed a new compound similarity measure. This measure is based on both knowledge poor and knowledge rich approaches to find word similarity. We also used Machine Learning Technique (Neural Network model) for combination of several similarity methods. We have compared our method with simple syntactic similarity measure. Our measure considerably improves the precision and recall of automatic... 

Currently there is no standard test collection for evaluation of Farsi information retrieval systems. In this paper we introduce Mahak, the first complete test collection generally available for evaluating Farsi information retrieval systems. We also discuss our construction process in detail. As a goal, we hope that Mahak will foster the development of Farsi information retrieval systems. © 2007 IEEE  

The paper aims at investigating the microstructure, failure mode transition, peak load and energy absorption of DP600 dual phase steel during the tensile-shear test. It was found that the welding current has profound effect on the load–displacement characteristics. In the low welding current, welds failed in interfacial failure mode. Increasing welding current resulted in sufficient weld nugget growth to promote double-sided pullout failure mode with improved mechanical properties. Further increase in the welding current caused expulsion and failure mode was changed to single-sided pullout with reduced energy absorption capability. It was found that the fusion zone size is the key parameter...