Sanjay Singh

Gauri Gupta, Krithika Ramesh, Sanjay Singh

With language models being deployed increasingly in the real world, it is essential to address the issue of the fairness of their outputs. The word embedding representations of these language models often implicitly draw unwanted associations that form a social bias within the model. The nature of gendered languages like Hindi, poses an additional problem to the quantification and mitigation of bias, owing to the change in the form of the words in the sentence, based on the gender of the subject. Additionally, there is sparse work done in the realm of measuring and debiasing systems for Indic languages. In our work, we attempt to evaluate and quantify the gender bias within a Hindi-English machine translation system. We implement a modified version of the existing TGBI metric based on the grammatical considerations for Hindi. We also compare and contrast the resulting bias measurements across multiple metrics for pre-trained embeddings and the ones learned by our machine translation model.

Ranjitha R. K., Sanjay Singh

Programming question and answer (Q & A) websites, such as Quora, Stack Overflow, and Yahoo! Answer etc. helps us to understand the programming concepts easily and quickly in a way that has been tested and applied by many software developers. Stack Overflow is one of the most frequently used programming Q\&A website where the questions and answers posted are presently analyzed manually, which requires a huge amount of time and resource. To save the effort, we present a topic modeling based technique to analyze the words of the original texts to discover the themes that run through them. We also propose a method to automate the process of reviewing the quality of questions on Stack Overflow dataset in order to avoid ballooning the stack overflow with insignificant questions. The proposed method also recommends the appropriate tags for the new post, which averts the creation of unnecessary tags on Stack Overflow.

Vikram Santhalia, Sanjay Singh

Internet and electronic media gaining more popularity due to ease and speed, the count of Internet users has increased tremendously. The world is moving faster each day with several events taking place at once and the Internet is flooded with information in every field. There are categories of information ranging from most relevant to user, to the information totally irrelevant or less relevant to specific users. In such a scenario getting the information which is most relevant to the user is indispensable to save time. The motivation of our solution is based on the idea of optimizing the search for information automatically. This information is delivered to user in the form of an interactive GUI. The optimization of the contents or information served to him is based on his social networking profiles and on his reading habits on the proposed solution. The aim is to get the user's profile information based on his social networking profile considering that almost every Internet user has one. This helps us personalize the contents delivered to the user in order to produce what is most relevant to him, in the form of a personalized e-magazine. Further the proposed solution learns user's reading habits for example the news he saves or clicks the most and makes a decision to provide him with the best contents.

Jnanamurthy HK, Sanjay Singh

Online reputation system is gaining popularity as it helps a user to be sure about the quality of a product/service he wants to buy. Nonetheless online reputation system is not immune from attack. Dealing with malicious ratings in reputation systems has been recognized as an important but difficult task. This problem is challenging when the number of true user's ratings is relatively small and unfair ratings plays majority in rated values. In this paper, we have proposed a new method to find malicious users in online reputation systems using Quality Repository Approach (QRA). We mainly concentrated on anomaly detection in both rating values and the malicious users. QRA is very efficient to detect malicious user ratings and aggregate true ratings. The proposed reputation system has been evaluated through simulations and it is concluded that the QRA based system significantly reduces the impact of unfair ratings and improve trust on reputation score with lower false positive as compared to other method used for the purpose.

Supriya D'Souza, Abhishek Rao, Amit Sharma et al.

Autonomous intelligent agent research is a domain situated at the forefront of artificial intelligence. Interest-based negotiation (IBN) is a form of negotiation in which agents exchange information about their underlying goals, with a view to improve the likelihood and quality of a offer. In this paper we model and verify a multi-agent argumentation scenario of resource sharing mechanism to enable resource sharing in a distributed system. We use IBN in our model wherein agents express their interests to the others in the society to gain certain resources.

Rohit Mishra, Md Zeeshan, Sanjay Singh

Two way buffer system is a system that exhibits transfer of data using two buffers concurrently. It includes processes that synchronize to exchange data with each other along with executing certain delays between these synchronizations. In existing Tiny Two Way Buffer System, both generators produce packets in half duplex manner in no time, deterministic time, and non deterministic time. Analysis of the model for above time options leads the model in deadlock. The model can be out of the deadlock if timings in the model is incorporated in alternative fashion. The generators produce packets after a delay of 10 seconds. However, generator one has an initial shift of 5 seconds after which it begins sending a packet every 10 seconds. Hence, initial delay for generator one is 15 seconds and for generator two it is 10 seconds. Due to this initial shift, both generators produce packets alternatively and is deadlock free as the packets do not meet at the same time instant. Moreover, the existing system model is not concurrent and hence takes more time for packet transfer in every iteration. In this paper we have proposed a model of buffer system using an additional dummy buffer for transfer of data packets, we thus checking the model with various time models as no time, deterministic time and non deterministic time. The results of proposed model under above time models are in deadlock. We achieve deadlock free situation by introducing appropriate delay in various buffers of the proposed system, the delay timing is nondeterministic time. The new approach speeds up the transfer of packets, as a result the transfer of data becomes concurrent, deadlock free and hence the model proposed is time efficient. Simulation results shows that the proposed two way buffer system is fully concurrent and time efficient as compared to the existing buffer system.

Vivek Vishal, Sagar Gugwad, Sanjay Singh

This paper addresses the issue of modeling and verification of a Multi Agent System (MAS) scenario. We have considered an agent based adaptive traffic signal system. The system monitors the smooth flow of traffic at intersection of two road segment. After describing how the adaptive traffic signal system can efficiently be used and showing its advantages over traffic signals with predetermined periods, we have shown how we can transform this scenario into Finite State Machine (FSM). Once the system is transformed into a FSM, we have verified the specifications specified in Computational Tree Logic(CTL) using NuSMV as a model checking tool. Simulation results obtained from NuSMV showed us whether the system satisfied the specifications or not. It has also showed us the state where the system specification does not hold. Using which we traced back our system to find the source, leading to the specification violation. Finally, we again verified the modified system with NuSMV for its specifications.