Related Papers Academic Research with Knowledge Graphs

  • The RelatedPapers is the easiest way to discover Academic Publications.
  • RelatedPaper can work with popular academic discovery tools to help visualize search results.
  • It uses knowledge graphs (semantic knowledge networks are a graph-based data model used to show data relationships with each other) in knowledge representation. The Knowledge Graph represents real-world entities (academic subjects) and their relationships.

Related Papers Academic Publication Search

  • Users can search through knowledge graphs in academic keywords and explore other topics/keywords related to the research field during the discovery.
  • Users can easily read the definition of the academic keyword and use discipline/sub-discipline filters for filtering in the knowledge graph.eractive
  • The most crucial component of ReletedPaper is shown most up-to-date academic papers with search areas.
  • Bilimsel bilginin sürekli değiştiği ve geliştiği bir zaman diliminde Related Papers kullanıcılarına akademik keşiflerin kapısını açacaktır.

Related Papers Most Recent Academic Publications

  • Graphical data help academics, researchers, and students access more profound knowledge when conducting interdisciplinary research.
  • Since the graphs are created entirely from the data obtained from the analysis of scientific publications, the graph automatically renews itself as the science is updated.
  • Advanced filtering is possible as all the publications in RelatedPaper are listed as disciplines and sub-disciplines.
  • After English and French, RelatedPaper now serves its users with Turkish Interface Support*.
  • *Publications are always received in their original language, and language support is interface related.

Related Papers Semantic Information Networks

  • Since the development of the Semantic Web with Web 2.0, infographics often reveal connections between concepts and entities. Today's popular search engines frequently use semantic information networks to display relevant results to users. Almost all social networks use these information graphs to make discoveries and friend suggestions to their users.
  • Using semantic information graphs in various machine learning algorithms, they detect entities' explicit and hidden properties. Information networks are frequently used in finance, health services, entertainment, and the market.
  • Related Paper anlamsal bilgi ağlarını kullanarak akademik yayınlarının anahtar kelimeleri ve bunların ilişkilerini gösteren tek akademik üründür.

Related Papers Traditional Search Method

  • Publications that enter the research area but are written with keywords that the user is unaware of and/or did not use in the search do not come.
  • Users cannot find related topics in the research area.
  • It is not possible to filter the research area by discipline and find the most used keywords in the research area.
  • The relationship between the keywords of the research subjects cannot be revealed.
  • The user cannot have information about the definitions/uses of keywords that interest the user.
  • The user cannot quickly see which publications are made on topics that interest him
  • Cannot see the relationship between words/topics visually.
Traditional Search Tool** Related Papers
Text-Based Search Supported.
Indexes Institutional Subscription Academic Databases.
Boolean Operators Supported.
Discipline and Sub-Discipline Filtering.
Visualizes Results with Knowledge Graphs.
Provides Related Keywords.
Gives Keyword Related Cookie Information.
Returns the Number of Publications in which The Keyword Is Mentioned.
Reveals The Subject and Relationship of Users and Publications with Each Other
Users Can Become a Member, Create Favorites and Alert Lists.
Personalized Article Recommendation to Users.
Easily Displays Images in Academic Publications.
** A tool like Google Scholar.