[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119808-en":3,"doc-seo-119808-105":29,"detail-sidebar-cat-0-en-105":82},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":11},119808,34359740700684,"Finn","https://ap-avatar.wpscdn.com/avatar/1f400023980c374ae676?_k=1777273430885731487",8,"Research & Report","Development Of An Efficient Search Engine Using Machine Learning Techniques - Paper","The paper addresses the challenge of retrieving relevant information from conventional search engines by proposing a machine-learning driven search engine. It targets higher accuracy and better relevance ordering of results by ranking more useful web pages at the top in response to user queries. The proposed approach combines techniques including weighted page ranking, graph neural networks, and XGBoost, and introduces LDA-based grouping for similar documents using ranking as an underlying basis.","Development Of An Efficient Search Engine Using Machine Learning Techniques  \nDr. G. SHARADA  \nProfessor, Dept of IT, Malla Reddy College of Engineering and Technology, Hyderabad, T.S, India  \nG. MANIKRISHNA  \nUG Student, Dept of IT, Malla Reddy College of Engineering and Technology, Hyderabad, T.S, India  \nK. MEGHANA  \nUG Student, Dept of IT, Malla Reddy College of Engineering and Technology, Hyderabad, T.S, India  \nMD. SULTAN FAROOQUI  \nUG Student, Dept of IT, Malla Reddy College of Engineering and Technology, Hyderabad, T.S, India  \nAbstract: The internet is the largest and most extensive source of information currently available. Search engines are often used because they allow users to get information from the World Wide Web. A search engine's fundamental function is to facilitate people's efforts to locate the information they are looking for. People use search engines because they are intended to provide them with the appropriate information according to a set of criteria, which may include quality and relevancy. Search engines offer a simple interface for searching for user queries and providing results in the form of the web URL of the appropriate web page. Nevertheless, obtaining relevant information via conventional search engines has become quite difficult in recent years. In order to conquer these obstacles, we are now using several machine learning strategies in the creation of a powerful search engine. This paper proposes a search engine that makes use of machine learning methods such as the weighted page ranking algorithm, the graph neural network, and XGBoost. The goal of this search engine is to place more relevant web pages at the top in response to user queries. Anyone is able to quickly determine which papers in a collection of documents are the most significant and access the data that is associated with those documents. It suggests a new model for grouping similar papers called LDA (Linear Discriminant Analysis), which is straightforward and uses that ranking asthe basis.  \nKeywords: – Search Engine; Machine Learning; Web Application; Search; Fuzzy Search; Inverted Index; Search Query;  \nI. INTRODUCTION  \nThe global web is basically an internet made up of separate computer systems and servers that are linked via a variety of technologies and methods. Each website consists of a large number of individual webpages that are continually generated and uploaded to the server. Hence, in order for a user to achieve oneof their goals, they need to know their blood type. Auser's search input may be parsed into a series of words that are then used as a keyword [1] . It's possible that the search input provided by a user might include syntactical errors. The specific need for search engines is about to emerge. Search engines provide a user with a user-friendly interface via which they may search up user queries and display the results. Web crawlers make it easier to compile information from several websites as well as the connections that are related to those websites. For the purpose of collecting information and data from the web and storing it in our database, this article will only use web crawlers. Indexer that sorts every phrase on every page and saves the following list of words in a very large repository; the indexer also maintains the terms in the correct order. It is very common to respond to the user's keyword and present the successful conclusion for that user's keyword.  \nUsing a variety of other algorithms included inside the question engine, the page ranking algorithm assigns a rating to the uniform resource locator. This ranking is shown within the question engine. Every application that provides users with search tools should absolutely prioritize ranking as one of the most important and fundamental practical considerations. As a result, a significant amount of information that involves analysis has been distributed in the realm of ranking. In spite of this, it is a well-known, undeniable truth that","cbCaieHymw7ELLVG","https://ap.wps.com/l/cbCaieHymw7ELLVG","pdf",507468,1,3,"English","en",105,"# Introduction\n## Web crawling and indexing\n## Ranking and relevance challenges\n# Problem Statement\n## Machine-learning powered retrieval goals","[{\"question\":\"How does the paper group similar documents?\",\"answer\":\"It suggests a new model for grouping similar papers called LDA (Linear Discriminant Analysis), which is described as straightforward and uses ranking as the basis.\"}]","Development Of An Efficient Search Engine Using Machine Learning Techniques - Paper | PDF",1785726412,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":77,"head_meta":79,"extra_data":81,"updated_unix":28},"development-of-an-efficient-search-engine-using-machine-learning-techniques-paper","",{"@graph":35,"@context":76},[36,52,67],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,49],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":21},"https://docshare.wps.com/document/research-report/",{"item":50,"name":13,"@type":42,"position":51},"https://docshare.wps.com/document/development-of-an-efficient-search-engine-using-machine-learning-techniques-paper/119808/",4,{"url":50,"name":13,"@type":53,"author":54,"headline":13,"publisher":56,"fileFormat":59,"inLanguage":23,"description":14,"dateModified":60,"datePublished":61,"encodingFormat":59,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":55},"Person",{"url":40,"name":57,"@type":58},"DocShare","Organization","application/pdf","2026-08-05","2026-08-03",true,{"@type":64,"interactionType":65,"userInteractionCount":20},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70],{"name":71,"@type":72,"acceptedAnswer":73},"How does the paper group similar documents?","Question",{"text":74,"@type":75},"It suggests a new model for grouping similar papers called LDA (Linear Discriminant Analysis), which is described as straightforward and uses ranking as the basis.","Answer","https://schema.org",{"og:url":50,"og:type":78,"og:title":13,"og:site_name":57,"og:description":14},"article",{"robots":80,"canonical":50},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":83},[84,88,92,96,101,106,111,114,119,122,126],{"id":20,"doc_module":4,"doc_module_name":45,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":46,"doc_module":4,"doc_module_name":45,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":51,"doc_module":4,"doc_module_name":45,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":45,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":102,"doc_module":4,"doc_module_name":45,"category_name":103,"show_sort_weight":104,"slug":105},6,"Technology",50,"technology",{"id":107,"doc_module":4,"doc_module_name":45,"category_name":108,"show_sort_weight":109,"slug":110},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":45,"category_name":12,"show_sort_weight":112,"slug":113},30,"research-report",{"id":115,"doc_module":4,"doc_module_name":45,"category_name":116,"show_sort_weight":117,"slug":118},9,"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":45,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":123,"doc_module":4,"doc_module_name":45,"category_name":124,"show_sort_weight":123,"slug":125},10,"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":45,"category_name":128,"show_sort_weight":97,"slug":129},19,"General","general"]