1 research outputs found
Parsisanj: a semi-automatic component-based approach towards search engine evaluation
Accessing to required data on the internet is wide via search engines in the
last two decades owing to the huge amount of available data and the high rate
of new data is generating daily. Accordingly, search engines are encouraged to
make the most valuable existing data on the web searchable. Knowing how to
handle a large amount of data in each step of a search engines' procedure from
crawling to indexing and ranking is just one of the challenges that a
professional search engine should solve. Moreover, it should also have the best
practices in handling users' traffics, state-of-the-art natural language
processing tools, and should also address many other challenges on the edge of
science and technology. As a result, evaluating these systems is too
challenging due to the level of internal complexity they have, and is crucial
for finding the improvement path of the existing system. Therefore, an
evaluation procedure is a normal subsystem of a search engine that has the role
of building its roadmap. Recently, several countries have developed national
search engine programs to build an infrastructure to provide special services
based on their needs on the available data of their language on the web. This
research is conducted accordingly to enlighten the advancement path of two
Iranian national search engines: Yooz and Parsijoo in comparison with two
international ones, Google and Bing. Unlike related work, it is a
semi-automatic method to evaluate the search engines at the first pace.
Eventually, we obtained some interesting results which based on them the
component-based improvement roadmap of national search engines could be
illustrated concretely