B. Minaei - Academia.edu (original) (raw)

Papers by B. Minaei

Journal of AI and Data Mining, 2019

Context-aware systems must be interoperable and work across different platforms at any time and i... more Context-aware systems must be interoperable and work across different platforms at any time and in any place. Context data collected from wireless body area networks (WBAN) may be heterogeneous and imperfect, which makes their design and implementation difficult. In this research, we introduce a model which takes the dynamic nature of a context-aware system into consideration. This model is constructed according to the four-dimensional objects approach and three-dimensional events for the data collected from a WBAN. In order to support mobility and reasoning on temporal data transmitted from WBAN, a hierarchical model based on ontology is presented. It supports the relationship between heterogeneous environments and reasoning on the context data for extracting higher-level knowledge. Location is considered a temporal attribute. To support temporal entity, reification method and Allen’s algebra relations are used. Using reification, new classes Time_slice and Time_Interval and new at...

International Journal of Applied Operational Research - An Open Access Journal, 2014

Cold start is one of the main challenges in recommender systems. Solving sparsechallenge of cold ... more Cold start is one of the main challenges in recommender systems. Solving sparsechallenge of cold start users is hard. More cold start users and items are new. Sine many general methods for recommender systems has over fittingon cold start users and items, so recommendation to new users and items is important and hard duty. In this work to overcome sparse problem, we present a new method for recommender system based on tensor decomposition that use time dimension as independent dimension. Our method uses extra information of sequence of rating time which specify time duration of ratings. We test our method on dataset of Each Movie with 2 data types. One type has cold start users and items and another hasn’t cold start users and items. Result shows that using time dimension has more effect on cold start users and items than others.

Abstract - In this paper, we improve an object detection approach using spatial histogram feature... more Abstract - In this paper, we improve an object detection approach using spatial histogram features, by applying classifier ensemble. The spatial histogram features can preserve texture and shape information of an object, simultaneously. We train a hierarchical classifier by ...

Clustering technique is one of the most important techniques of data mining and is the branch of ... more Clustering technique is one of the most important techniques of data mining and is the branch of multivariate statistical analysis and a method for grouping similar data in to same clusters. With the databases getting bigger, the researchers try to find efficient and effective clustering methods so that they can make fast and real decisions. Thus, in this paper, we proposed an improved ant system-based clustering algorithm (IASC) in order to providing the fast clusters with high accuracy. The goal of clustering analysis is to group similar objects together. There are many methods being applied in clustering analysis, like hierarchical clustering, partition-based clustering, density-based clustering, and artificial intelligence-based clustering. The ant colony system (ACS) is one of the newest meta-heuristics for combinatorial optimization problems, and this study uses the ant colony system to find the clusters effectively. The IASC algorithm is including four sub-procedures, that is...

Lecture Notes in Computer Science, 2010

In this paper a new Reinforcement Learning algorithm was proposed. Q learning is a useful algorit... more In this paper a new Reinforcement Learning algorithm was proposed. Q learning is a useful algorithm for agent learning in nondeterministic environment but it is a time consuming algorithm. The presented work applies an evolutionary algorithm for improving Reinforcement Learning algorithm.

Information Retrieval Technology, 2011

... from English-Persian Translated Documents* Mohammad Sadegh Rasooli, Omid Kashefi, and Behrouz... more ... from English-Persian Translated Documents* Mohammad Sadegh Rasooli, Omid Kashefi, and Behrouz Minaei-Bidgoli ... Persian is a variation of Arabic-script language that is mostly spoken in Iran, Afghanistan, Tajikistan and some parts of India and Pakistan. ...

2009 14th International CSI Computer Conference, 2009

In this paper, we proposed a new feature subset selection approach. In proposed approach first, t... more In this paper, we proposed a new feature subset selection approach. In proposed approach first, the entire dataset are classified and the best number of clusters over it are found according to silhouette value. Then according to this value, each feature is alone classified with the same cluster number and accordingly the proposed entropy fuzzy measure is found for them.

2008 Fourth International Conference on Networked Computing and Advanced Information Management, 2008

In this paper, a new method for improving the performance of combinational classifier systems is ... more In this paper, a new method for improving the performance of combinational classifier systems is proposed. The main idea behind this method is heuristic retraining of artificial neural network (ANN). In combinational classifier systems, whatever the more diversity in results of base ...

2011 7th International Conference on Natural Language Processing and Knowledge Engineering, 2011

In computers era, the flow of producing digital documents simply overwhelmed the traditional manu... more In computers era, the flow of producing digital documents simply overwhelmed the traditional manual spell checking, the worst new type of misspelling called typographical errors have been created by machinery text production and management. Therefore, referring to human intolerable load of digital text&amp;#39;s spell checking also the irrecusable ability of computers, including accuracy and speed, automatic spell checking using computer

... Understanding of Wiki data Mohsen Khoshgoftar, Behrouz Minaei , and Ahmad Faraahi ... ... more ... Understanding of Wiki data Mohsen Khoshgoftar, Behrouz Minaei , and Ahmad Faraahi ... Wikipedia. Available at URL: http://en.wikipedia.org/wiki/Main_Page.Accessed sep 16, 2010. [4] Holloway, Todd, Bozicevic, Miran and Borner, Katy. ...

Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, 2004. IRI 2004.

An important goal of data mining is to discover the unobvious relationships among the objects in ... more An important goal of data mining is to discover the unobvious relationships among the objects in a data set. Web-based educational systems collect vast amounts of data on user patterns, and data mining methods can be applied to these databases to discover interesting associations between student attributes, problem attributes, and solution strategies. In this paper, we propose a framework for the discovery of interesting association rules within a web-based educational system. A hybrid measure of subjective and objective measure for rule interestingness is proposed which is called contrasting rules. Contrasting association rule is one in which a conjunction of attributes is compared for complementary subsections of a data set. We provide a new algorithm for mining contrasting rules that can improve these systems for both teachers and studentsallowing for greater learner improvement and more effective evaluation of the learning process. A larger advantage of developing this approach is its wide application in any other data mining application.

2008 International Conference on Computer and Electrical Engineering, 2008

This paper proposes an interactive approach for region-based image clustering and retrieval. By p... more This paper proposes an interactive approach for region-based image clustering and retrieval. By performing clustering before image retrieval, the search space can be reduced to those clusters that are close to the query target. First, the image is segmented to regions by using an unsupervised segmentation method. This is an area where a vast number of regions are involved. To reduce search space for region-based image retrieval, we use clustering based on genetic algorithm. Fuzzy similarity is used in order to compute the similarity of two images. Moreover, a two-class SVM is trained based on user interests to improve image retrieval. Experiments were performed on COREL image database and show the effectiveness of the proposed approach.

Dynamic optimization in which global optima and local optima change over time is always a hot res... more Dynamic optimization in which global optima and local optima change over time is always a hot research topic. It has been shown that particle swarm optimization works well when facing dynamic environments. On the other hand, a learning automaton can be considered as an intelligent tool (agent) which can learn what action is the best interacting with its environment. The great deluge algorithm is also a search algorithm applied to optimization problems. All these algorithms have their drawbacks and advantages. This paper explores how one can combine these algorithms to reach better performance in dynamic spaces. Indeed a learning automaton is employed per particle in the swarm to decide whether its particle updates its velocity (and consequently its position) considering the best global particle position, local particle position or a combined position extracted out of global and local particle position. Water level in the deluge algorithm is used in the progress of the algorithm. Exp...

Adaptive and Natural Computing Algorithms, 2011

Invariants could be defined as prominent relation among program variables. Daikon software has im... more Invariants could be defined as prominent relation among program variables. Daikon software has implemented a practical algorithm for invariant detection. There are several other dynamic approaches to dynamic invariant detection. Daikon is considered to be the best software developed for dynamic invariant detection in comparing other dynamic invariant detection methods. However this method has some problems. Its time order is

In this paper, a new method to improve sites access filtering is presented. This method is based ... more In this paper, a new method to improve sites access filtering is presented. This method is based on web visitor behavior analysis. In order to analyze the behavior of users, A procedure is proposed following which, based on the information in the log files of proxy servers, user's behavior history was extracted and stocked in a data bank by a data-mining engine. Authorized or unauthorized access to the desired page, when a user requests a new page, is reported after investigation of the user's behavior history. The above architecture was tested, using data from one of the globally credible sites, and the results were analyzed.