Sharif Digital Repository

This paper presents UOWD-Sharif team's approach for XML information retrieval. This approach is an extension of PLIR which is an experimental knowledge-based information retrieval system. This system like PLIR utilizes plausible inferences to first infer the relevance of sentences in XML documents and then propagates the relevance to the other textual units in the document tree. Two approaches have been used for propagation of confidence. The first approach labeled "propagate-DS" first propagates the confidence from sentences to upper elements and then combines these evidences by applying Dempster-Shafer theory of evidence to estimate the confidence in that element. The second approach... 

We consider the problem of private information retrieval (PIR), where a single user with private side information (PSI) aims to retrieve multiple files from a library stored at some servers. We assume that the side information (SI) at the user includes a subset of files stored privately. Moreover, the identity of requests and side information at the user are not revealed to any of the servers. The problem involves finding the minimum load transmitted from the servers to the user such that the requested files can be decoded with the help of received data and side information. By providing matching lower and upper bounds for certain regimes, we characterize the minimum load imposed on all the... 

Rank aggregation, that is merging multiple ranked lists, is a pivotal challenge in many information retrieval (IR) systems, especially in distributed IR and multilingual IR. From the evaluation point of view, being able to calculate the upper-bound of performance of the final aggregated list lays the ground for evaluating different aggregation strategies, independently. In this paper, we propose an algorithm based on dynamic programming which, using relevancy information, obtains the aggregated list with the maximum performance that could be possibly achieved by any aggregation strategy. We also provide a detailed proof for the optimality of the result of the algorithm. Furthermore, we... 

In this investigation, the idea of Visual Working Memory (VWM) mechanism modeling based on versatile fuzzy method; Active Learning method, is presented. Visual information process; retrieving and learning rely on the use of Ink Drop Spread (IDS) and Center of Gravity (COG) as spatial density convergence operators. IDS modeling is characterized by processing that uses intuitive pattern information instead of complex formulas, and it is capable of stable and fast convergence. Furthermore, because it approves that distortion in retrieving irrelative data is adaptive to avoid storing lots of repetitive external information in daily visualization. Subsequently, this distortion is analyzed via two... 

We consider the problem of private information retrieval (PIR) where a single user with private side information aims to retrieve multiple files from a library stored (uncoded) at a number of servers. We assume the side information at the user includes a subset of files stored privately (i.e., the server does not know the indices of these files). In addition, we require that the identity of requests and side information at the user are not revealed to any of the servers. The problem involves finding the minimum load to be transmitted from the servers to the user such that the requested files can be decoded with the help of received and side information. By providing matching lower and upper... 

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. In addition, we have used different methods for constructing Mahak qrels and we have compared performance of these methods  

In this paper, we propose a new method for automatic news event detection. An event is a specific happening in a particular time and place. We propose a new model in this paper to detect news events using a label based clustering approach. The model takes advantage of the fact that news events are news clusters with high internal similarity whose articles are about an event in a specific time and place. Since news articles about a particular event may appear in several consecutive days, we developed this model to be able to distinguish such events and merge the corresponding news articles. Although event detection is propounded as a stand alone news mining task, it has also applications in... 

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  

Various methods using different measures have been proposed for ontology alignment. Therefore, it is necessary to evaluate the effectiveness of such measures to select better ones for more quality alignment. Current approaches for comparing these measures, are highly dependent on alignment frameworks, which may cause unreal results. In this paper, we propose a framework independent evaluation method, and discuss results of applying it to famous existing string measures. © Springer-Verlag Berlin Heidelberg 2006  

The choice of technology to transport passengers in large metropolitan areas is an important issue everywhere. There are many factors involved in this choice. This paper deals with the possibility of the objective use of available information in the analysis of the suitability of a rail public transport system for a city. A database has been made from publications on public city transportation and country level information. Logit models of choice have been calibrated by the maximum likelihood and nonlinear least square methods based on the acquired information. Each city is treated as an "individual", choosing rail or non-rail modes for its trips. Only cities with a population of more than... 

With the extensive growth in information, text classification as one of the text mining methods, plays a vital role in organizing and management information. Most text classification methods represent a documents collection as a Bag of Words (BOW) model and then use the histogram of words as the classification features. But in this way, the number of features is very large; therefore performing text classification faces serious computational cost problems. Moreover, the BOW representation is unable to recognize semantic relations between words. Recently, topic-model approaches have been successfully applied for text classification to overcome the problems of BOW. Our main goal in this paper... 

The widespread use of cloud computing services raises the question of how one can delegate the processing tasks to the untrusted distributed parties without breaching the privacy of its data and algorithms. Motivated by the algorithm privacy concerns in a distributed computing system, in this paper, we introduce the private function retrieval (PFR) problem, where a user wishes to efficiently retrieve a linear function of K messages from N non-communicating replicated servers while keeping the function hidden from each individual server. The goal is to find a scheme with minimum communication cost. To characterize the fundamental limits of the communication cost, we define the capacity of PFR...