{"id":{"repo_id":"debrecen","oai_identifier":"oai:dea.lib.unideb.hu:2437/331746"},"canonical_url":"https://search.dev.ndltd.org/etd/debrecen/oai:dea.lib.unideb.hu:2437/331746","repository":{"repo_id":"debrecen","name":"University of Debrecen","base_url":"https://dea.lib.unideb.hu/server/oai/request"},"display":{"title":"Content based recommendation system & android application","abstract":"Rising of the recommendation systems has come into markets which gives the suggestions to users. A recommendation system is a type of information filtering system that attempts to forecast a user need or we can say preference for an item. Although every application serves a unique function, not every application can be tailored to a specific context of usage., I will try to investigate and build a recommendation system for the movies also i have another objective is to build a full-fledged android based mobile application through which users can try our recommendation system most probably i will use a Content-Based recommender system which one of the most popular types of recommendation system. Content-based filtering aims to calculate a user's characteristics or behavior based on the features of an item to which the user responds positively and need to have huge dataset. A content-based recommender system generates recommendations based on the metadata of objects or people. based on the user search or if we have a history of previously watched movies. My objective is to make a working application with the recommender system integrated together. if I will not be able to succeed in running ML model in android phone itself then I will make a Backend for the recommender system","abstract_html":"Rising of the recommendation systems has come into markets which gives the suggestions to users. A recommendation system is a type of information filtering system that attempts to forecast a user need or we can say preference for an item. Although every application serves a unique function, not every application can be tailored to a specific context of usage., I will try to investigate and build a recommendation system for the movies also i have another objective is to build a full-fledged android based mobile application through which users can try our recommendation system most probably i will use a Content-Based recommender system which one of the most popular types of recommendation system. Content-based filtering aims to calculate a user's characteristics or behavior based on the features of an item to which the user responds positively and need to have huge dataset. A content-based recommender system generates recommendations based on the metadata of objects or people. based on the user search or if we have a history of previously watched movies. My objective is to make a working application with the recommender system integrated together. if I will not be able to succeed in running ML model in android phone itself then I will make a Backend for the recommender system","abstract_has_math":false,"creators":["Thakur, Devansh"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"DE--Informatikai Kar","school":null,"contributors":[],"advisors":["Adamkó, Attila"],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-27T19:13:35Z","subjects":["Recommender system","Android","Machine Learning"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2437/331746","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Adamkó, Attila"]},{"key":"dc:contributor.department","label":"Department","values":["DE--Informatikai Kar"]},{"key":"dc:creator","label":"Author","values":["Thakur, Devansh"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2022-04-27T08:01:41Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-04-27T08:01:41Z"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Recommender system","Android","Machine Learning"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/2437/331746"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Rising of the recommendation systems has come into markets which gives the suggestions to users. A recommendation system is a type of information filtering system that attempts to forecast a user need or we can say preference for an item. Although every application serves a unique function, not every application can be tailored to a specific context of usage., I will try to investigate and build a recommendation system for the movies also i have another objective is to build a full-fledged android based mobile application through which users can try our recommendation system most probably i will use a Content-Based recommender system which one of the most popular types of recommendation system. Content-based filtering aims to calculate a user's characteristics or behavior based on the features of an item to which the user responds positively and need to have huge dataset. A content-based recommender system generates recommendations based on the metadata of objects or people. based on the user search or if we have a history of previously watched movies. My objective is to make a working application with the recommender system integrated together. if I will not be able to succeed in running ML model in android phone itself then I will make a Backend for the recommender system"]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["MSc/MA"]},{"key":"dc:title","label":"Title","values":["Content based recommendation system & android application"]}]}],"canonical_facts":{"dc:contributor.advisor":["Adamkó, Attila"],"dc:contributor.department":["DE--Informatikai Kar"],"dc:creator":["Thakur, Devansh"],"dc:date.accessioned":["2022-04-27T08:01:41Z"],"dc:date.available":["2022-04-27T08:01:41Z"],"dc:description.abstract":["Rising of the recommendation systems has come into markets which gives the suggestions to users. A recommendation system is a type of information filtering system that attempts to forecast a user need or we can say preference for an item. Although every application serves a unique function, not every application can be tailored to a specific context of usage., I will try to investigate and build a recommendation system for the movies also i have another objective is to build a full-fledged android based mobile application through which users can try our recommendation system most probably i will use a Content-Based recommender system which one of the most popular types of recommendation system. Content-based filtering aims to calculate a user's characteristics or behavior based on the features of an item to which the user responds positively and need to have huge dataset. A content-based recommender system generates recommendations based on the metadata of objects or people. based on the user search or if we have a history of previously watched movies. My objective is to make a working application with the recommender system integrated together. if I will not be able to succeed in running ML model in android phone itself then I will make a Backend for the recommender system"],"dc:description.degree":["MSc/MA"],"dc:identifier.uri":["http://hdl.handle.net/2437/331746"],"dc:language.iso":["en"],"dc:subject":["Recommender system","Android","Machine Learning"],"dc:title":["Content based recommendation system & android application"]},"updated_at":"2026-07-27T19:13:35Z"}