Mohammad Najmud Doja

Feature and Opinion Mining for Customer Review Summarization

In this paper, we present an opinion mining system to identify product features and opinions from review documents. The features and opinions are extracted using semantic and linguistic analysis of text documents. The polarity of opinion sentences is established using polarity scores of the opinion words through Senti-WordNet to generate a feature-based summary of review documents. The system is also integrated with a visualization module to present feature-based summary of review documents in a comprehendible way.

Finding Time Quantum of Round Robin CPU Scheduling Algorithm Using Fuzzy Logic

In Round Robin Scheduling the time quantum is fixed and then processes are scheduled such that no process get CPU time more than one time quantum in one go. If time quantum is too large, the response time of the processes is too much which may not be tolerated in interactive environment. If time quantum is too small, it causes unnecessarily frequent context switch leading to more overheads resulting in less throughput. In this paper a method using fuzzy logic has been proposed that decides a value that is neither too large nor too small such that every process has got reasonable response time and the throughput of the system is not decreased due to unnecessarily context switches.

Real Time Multigraphs for Communication Networks: An Intuitionistic Fuzzy Mathematical Model

Many problems of computer science, communication network, transportation systems, can be modeled into multigraphs (or graphs) and then can be solved. Nowadays, the networks are expanding very fast in huge volumes in terms of their nodes and the connecting links. For a given alive network, in many situations, its complete topology may not be always available to the communication systems at a given point of time because of the reason that few or many of its links (edges/arcs) may be temporarily disable owing to damage or attack or blockage upon them and of course they are under repair at that point of time. Such cases are now so frequent that it calls for rigorous attention of the researchers, in particular to those who are concerned with Quality of Service (QoS) while in a network. Even in most of the cases the cost parameters corresponding to its links are not crisp numbers, rather intuitionistic fuzzy numbers (or fuzzy numbers). Thus at any real time instant, the complete multigraph is not available but a submutigraph of it is available to the system for executing its communication or transportation activities. Under such circumstances, none of the existing algorithms on Shortest Path Problems (SPP) can work. In this study the authors propose a mathematical model for such types of multigraphs to be called by ‘Real Time Multigraphs’ (RT-multigraphs) in which all real time information (being updated every q quantum of time) are incorporated so that the communication/transportation system can be made very efficiently with optimal results. It is a kind of intuitionistic fuzzy mathematical model being the most generalized form of the crisp multigraphs. As a special case, RT-multigraphs reduce to the case of ‘RT-graphs’. Finally an intuitionistic fuzzy method is developed to solve the shortest path problem in a RT-Multigraph. As a special case the problem reduces to fuzzy shortest path problem in a RT-Multigraph.

An algorithm for extracting intuitionistic fuzzy shortest path in a graph

We consider an intuitionistic fuzzy shortest path problem (IFSPP) in a directed graph where the weights of the links are intuitionistic fuzzy numbers. We develop a method to search for an intuitionistic fuzzy shortest path from a source node to a destination node. We coin the concept of classical Dijkstras algorithm which is applicable to graphs with crisp weights and then extend this concept to graphs where the weights of the arcs are intuitionistic fuzzy numbers. It is claimed that the method may play a major role in many application areas of computer science, communication network, transportation systems, and so forth. in particular to those networks for which the link weights (costs) are ill defined.

Improving the performance of fair share scheduling algorithm using fuzzy logic

In Fair Share scheduling shares of CPU time for each group of processes is fixed and then accordingly processes from each group are allocated CPU for their execution. We have proposed a FIS using which CPU share of group of Processes will be decided dynamically. FIS has also been constructed for scheduling within the group to minimize the overheads. For scheduling within the group Fair Share Scheduling algorithm uses Round Robin scheduling. If the process do not complete its execution within the time quantum, the process is put at the end of ready queue and process switch occurs where state of the running process is put onto stack and the state of the next process is taken from the stack and its execution is resumed. If the time required for the running process is slightly more than time quantum by a fraction, even then process is preempted and context switch occurs. This results into more waiting time for that process and more overheads due to unnecessary context switch. In this paper an algorithm using fuzzy logic has also been proposed that tries to remove these two problems.

Low energy adaptive stable energy efficient (LEASE) protocol for wireless sensor network

Energy efficiency is one of the important considerations while designing an algorithm for wireless sensor network due to confined energy of sensor nodes. One of the best applications of wireless sensor network is unattended operation. In such application, it is not feasible to replace or recharge sensors frequently. Algorithm with uneven energy dissipation is not suitable for such applications. LEACH is a good solution to balance the load of network but still has some disadvantages. In this paper, we have proposed cluster based load balancing so that the energy dissipation rate of the nodes are almost similar. Cluster head selection is based on the parameters like residual energy, distance to base station and proximity to neighbours in order to balance the load among the sensors in the network. Simulation results show that proposed scheme has better stability period and balances the load of the network with prolong lifetime.

Opinion Mining Using Frequent Pattern Growth Method from Unstructured Text

In the last one decade, the area of opinion mining has experienced a major growth because of the increase in online unstructured data which are contributed by reviewers over different topics and subjects. These data sometimes become important for users who want to take their decision based on opinions of actual users of the product. In this paper, we present the FP-growth method for frequent pattern mining from review documents which act as a backbone for mining the opinion words along with their relevant features by experimental data over two different domains which are very different in their nature.

Generalized Query Processing Mechanism in Cloud Database Management System

This is an epoch of Big data, Cloud computing, Cloud Database Management techniques. Traditional database approaches are not suitable for such colossal amount of data. To overcome the limitations of RDBMS, Map Reduce codes can be considered as a probable solution for such huge amount of data processing. Map Reduce codes provide both scalability and reliability. Users till date can work snugly with traditional Database approaches such as SQL, MYSQL, ORACLE, DB2, etc., and they are not aware of Map Reduce codes. In this paper, we are proposing a model which can convert any RDBMS queries to Map Reduce codes. We also gear optimization technique which can improve the performance of such amalgam approach.

ANFIS Aided AODV Routing Protocolfor Mobile Ad Hoc Networks

Communication between mobile nodes is the key purpose of Mobile Ad Hoc Networks (MANETs). However, increase in the traffic leads to multiple challenging issues like congestion among nodes, consumption of more bandwidth, high energy requirement and low efficiency output. A powerful solution to these issues of the MANET is to use intelligent routing protocols. The Adaptive Neural Fuzzy Inference System (ANFIS) is one of those advanced technique which adjust itself according to the change in system. Therefore, the use of ANFIS in routing protocol results in efficient guiding of packet from source to destination. In this paper, the route selection mechanism of traditional Ad Hoc on Demand Distance Vector (AODV) routing protocol is improved with the use of ANFIS having input attributes hop count, energy consumption and delay. Simulation of the proposed ANFIS Aided AODV (AAODV) shows the clear improvement in quantitative parameters like Throughput and Packet Delivery Ratio (PDR).

Neighborhood Topology to Discover Influential Nodes in a Complex Network

This paper addresses the issue of distinguishing influential nodes in the complex network. The k-shell index features embeddedness of a node in the network based upon its number of links with other nodes. This index filters out the most influential nodes with higher values for this index, however, fails to discriminate their scores with good resolution, hence results in assigning same scores to the nodes belonging to same k-shell set. Extending this index with neighborhood coreness of a node and also featuring topological connections between its neighbors, our proposed method can express the nodes influence score precisely and can offer distributed and monotonic rank orders than other node ordering methods.