Turkish Journal of Computer and Mathematics Education Vol.12 No.2 (2021), 2077-2085 Research Article 2077 Elucidating Complex Queries Based on Curtailing Technique for Effective Green Communication Anshy Singh 1 , Himanshu Sharma 2 1 Department of Computer Engineering and Application, GLA University, Mathura, India 2 Department of Computer Engineering and Application, GLA University, Mathura, India Mathura.anshy.singh@gla.ac.in 1 , Mathura.himanshu.sharma@gla.ac.in 2 Article History: Received: 10 November 2020; Revised: 12 January 2021; Accepted: 27 January 2021; Published online: 05 April 2021 Abstract: A system has been developed to improve on the quality of search for which we have replaced the present searching methods by our procedure Explore Scheme, which greatly increases the utility of Web, over what is available today. None of the Search Techniques is able to deal effectively and efficiently with the huge volume of information posted on World Wide Web. In the current searching methodology, our proposed system emphasizes on enhancing the searching method by our proposed Explore-Scheme procedure, which provides solution to the complex queries based on contextual expansion. It is our observation that in investigating relevance feedback questions (both existing and new), we will implement the Explore- Scheme algorithm on web in this way we can enhance the ability which will give rise to the information which is good, of some use and relevant. Currently, we are implementing the system that is able to demonstrate important properties of the presented approach. Our method reduces the word to its atomic part thus curtailing the size of the dictionary by saving Storage space and processing time enhancing the processing speed of query. We can finally say that our proposed algorithm will definitely improve the information retrieval capabilities and are able to deal effectively and efficiently with the huge volume of information posted on World Wide Web. Keywords: Information Retrieval, Indexing, Stemming, Content-based Search, Data Clustering 1. Introduction Each human being after surfing the web or utilizing the corporate intranet forms an opinion regarding the ways and the means which develops a “good” Web founded systems as well as applications [1]. The perception of each human being differs [2]. There are the people who enjoy vibrant graphics, and then there are the others who wish to have lucid text [3,4,5]. There are few people who ask for the ample information while there are the few who aim at a presentation which his abbreviated [6]. In reality, the point of view of the people who use “goodness” might be more important than any technical discussion of Web applications quality [7,8,9]. Retrieval of information, utility, effectiveness as well as functionality gives a good ground to assess the merit of system which is web based [10,11,12]. The steep development of the database in most of the avenues of human action has designed a want for renewed tools which will turn data into concrete knowledge [13,14,15]. The scholars from several technological avenues like machine learning, statistical data analysis, pattern recognition, information retrieval and information extraction as well as neural network have come forward to meet the demand have been searching formulae and ideas [16 -19]. Such efforts have pioneered us to a research avenue which is generally addressed as date mining [20]. It may be defined as the concrete extraction of non-obvious rooting out the underlined which is unknown before and has the potential of beneficial information from the data that is given [21, 22]. In fact till now, maximum task in the discovery of knowledge in the databases has been related with data which is structured [23]. Nevertheless, maximum information can be accessed in the form of given text as in the documents, emails, web presentations and manuals etc [24]. This form of information comprises the restricted internal structure obviously different from the tabular information stored in Conventional Databases [25]. Information retrieval consequences are generally given to the users like a documents based on rank which is in the decreasing order of relevance. This system incorporates the feedback which is based on the relevance of the user where he or she can avail the opportunity to evaluate the list of ranks and figure out the documents which are important to answer the query of the users and the one which do not [26]. Afterwards the information is utilized by the feedback algorithm and it causes a new rank document which is displayed to the user and this process repeats itself. The effectiveness of relevance feedback is explored in helping the users to explore a target document which is decided already. Moreover, an innovative approach is devised by utilizing a fact that, as the number of the options of the user is many, it is still found to be limited. In this way it is possible to devise and peruse the whole space of feasible options of the user for a cycle of feedback on the importance of the document which is presented and achieve the upper bound the efficiency of the executed relevant feedback algorithm. We can interpret the upper bound as the end result obtained by an ideal user. In fact, the options of this ideal user enable