1 results listed
With the advancing technology, the storage of large
amounts of data has become possible. Unstructured nature of data
makes it difficult to access. Many sectors demand access to
specific information within their area. Thus, it has emerged the
concept of vertical search engine.
In our study, a crawler was designed to filter reliable sites. The
designed crawler only adds results related to academic
publications to the database. Naive Bayes classifier algorithm was
employed to identify the science branch of an academic
publication by using its abstract. According to our experiments,
the accuracy rate of developed vertical search engine was 70%.
The application is designed in a way that it can self-learn so that
the success rate can increase.
International Conference on Cyber Security and Computer Science
ICONCS
Asım Yüksel
Muhammed Ali Karabıyık