**Abstract**

The explosion of affluent social networks, online communities, and jointly generated information resources has accelerated the convergence of technological and social networks producing environments that reveal both the framework of the underlying information arrangements and the collective formation of their members. In studying the consequences of these developments, we face the opportunity to analyze the POD repository at unprecedented scale levels and extract useful information from query log data. This chapter aim is to improve the performance of a POD repository from a different point of view. Firstly, we propose a novel query recommender system to help users shorten their query sessions. The idea is to find shortcuts to speed up the user interaction with the open data repository and decrease the number of queries submitted. The proposed model, based on pseudorelevance feedback, formalizes exploiting the knowledge mined from query logs to help users rapidly satisfy their information need.

**Keywords:** Data Mining, Query, Public Open Data, Social Network, Knowledge Extraction

### **1. Introduction**

SNS (Social networking services) is online services, platforms, or sites designed to support the development of Internet-based communities or community links between, for instance, individuals who often regularly interact with hobbies, experiences, and emotional interactions. SNS includes an account of every member and its community ties and a range of additional capabilities (typically a biography). A significant number of SNS are social media and allow consumers to communicate Online like e-mail and automatic messages. While SNS is often an individualcentered service in a broad context, social media facilities are a team. Social media platforms may be regarding constitute SNS. Online Communities enable individuals inside individual unique systems to exchange opinions, tasks, experiences, and goals.

Social networks communicate to interact in many innovative approaches, such as shows, hashtags, perform and engages electronically, revealing further cooperation and projected benefit that could scarcely imagine only a short time before. Online communities can play a significant role in the organizational processes as well as helping to develop company concepts and emotional responses and give up different prospects for the examination of social interactions and social behavior.

Presently, people rely on social media and its vast and diverse wealth and have progressively penetrated each human living area. Increasingly individuals prefer to engage valuable time on social media to develop a significant social entertaining community and again try to communicate with each other so often that the interaction around them is robust. POD repository analytics is perhaps a commonly used scientific and commercial approach for investigating the social media of interpersonal, organizational, and corporate links. The necessity for solid knowledge in DPO analysis has lately increased with ready availability to computational power and the rise of social popular social networking platforms such as LinkedIn, Twitter, Netlog, and more.

Twitter social network by study the contents of the tweets and the links between the tweets to extract knowledge from log data. By selecting buzzwords, began the 'Twitter review and then collecting all Twitter posts (Tweets) correlated to the keywords. It is a social-economical problem in India. Mining the query log based on social networks like Facebook, Twitter, etc. Study and address the discovery, access, and citation of POD repositories like Twitter data sets; and strengthening educational programs of academics of current and future generations specializing in such areas. This is an auspicious time for extracting useful information from social media query log data. Substantial efforts to decipher large amounts of data are steps towards complete search log records integrating POD repository analysis. From these data sets, we extract valuable knowledge.

The search log obtained by user actions with the Public Open Data (POD) database is an excellent data collection for improving its efficiency and the effectiveness of the online community. The data in the user input logs are gathering from individuals who communicate on online platforms. The search log assessment is complicating due to the variety of customers and diverse resources. As a result, numerous scientific articles written about query log analysis.

The word "data set" can also describe the data in a set of specifically relevant tables that correlate to a specific investigation or occurrence. Records generated by satellites testing hypotheses using devices aboard communications satellites are one instance of such a category. A data source is the standard measurement for data provided in a POD repository in the open data domain. Over a quarter a million datasets are gathering on the European Open Data platform. Alternative interpretations were presented in this area, although there is presently no accurate statement. Various difficulties (relevant data resources, non-relational datasets, etc.) make reaching a compromise more challenging. The utilization of query logs for knowledge discovery improves the speed of the POD repositories and improves the use of open data source capabilities.

POD repository analysis and mining for valuable extract knowledge from query log data. We perform on knowledge discovery, ML or similar approaches, challenges connected to pre-processing and model assessment, for data sets (web usage log files, query logs, collection of documents), and collaborative data (images, videos, and their explanations multi-channel handling data). We summarize the fundamental results concerning query logs: analyses, procedures used to retrieve knowledge, the outstanding results, most practical applications, and open issues and possibilities that remain to be studied. We discuss how the retrieved knowledge can be utilized to progress different social media class features, mainly its effectiveness and efficiency.

In addition, several concurrent inquiries of multiple distinct users are addressing by business social networks. The query stream has simultaneously been defining by a stop-time rate, making it impossible for the POD repository to generate massive query load times without over-sizing [1]. Web Search engines Query Logs Social

Network Analysis [2], Web search engine quality approaches developed for query logs, November 2013.
