BY MURAT AKKAYA
AZRA ENTERPRISE SEACH ENGINE DEVELOPED IN GIRNE AMERICAN UNIVERSITY,
FACULTY OF BUSINESS AND ECONOMICS
The amount of information available to a person is growing day by day; hence retrieving the correct information in a timely manner plays a very important role.
The AZRA Engine is indexing document collections and fetching the right information with the help of a database. The primary role of a database is to store the additional information which may be or may not be available in the document collection by itself.
This enterprise search engine addresses the problem of information overload by improving the retrieval performance of enterprise search. Engine is created by developing an intelligent recommender system which is able to filter out the irrelevant the search result and display those documents and experts which are relevant to the user query. A list of experts included those people who are most likely to have the required knowledge of the query topic and have searched/read those documents before. And this research focused on educational organization because the information has become one of the important resources of this type of organisations. Consequently, our direction came to develop an intelligent and integrated approach to solve many problems which are facing such organisations during searching processes.
This enterprise search engine addresses the problem of information overload by improving the retrieval performance of enterprise search. – Assoc. Prof. Dr. Murat Akkaya
AZRA search engine was developed under the supervision of the Dean of Faculty of Business & Economics Assoc. Prof. Dr. Murat Akkaya in GAU , Faculty of Business and Economics and has been accepted as a Ph.D. thesis of PhD student Khalid Awad Altarawneh in the main field of Management Information Systems entitled An Intelligent Recommender System based on Collaborative Filtering for Enterprise Information Search for Educational Environment as a special intelligent integrated fuzzy approach based on Lucene by capturing the implicit and explicit feedback from users during the searching process to assets their performance.
The indexing of document collection is performed by Lucene.net, while the search application is strongly integrated with a database. In this report a highly efficient, scalable, customized search tool is built using Lucene. The search tool is capable of indexing and searching databases, PDF documents, word documents, RTF, PPT documents, XLS documents, text files, etc. Enterprise search engine provides C#-based indexing and search technology, as well as spellchecking, hit highlighting and advanced analysis/tokenization capabilities.
Solr is a high performance search server built using Lucene Core, with XML/HTTP and JSON/Python/Ruby APIs, hit highlighting, faceted search, caching, replication, and a web admin interface. Lucene.NET itself is a class library, not an executable.
The amount of information available to a person is growing day by day; hence retrieving the correct information in a timely manner plays a very important role. – Assoc. Prof. Dr. Murat Akkaya
AZRA system is to illustrate how to use Lucene to create, populate, and search an index. For clarity, import statements and exception handling have been omitted from the sample programs. In these illustrations, the search index was stored in the huge file system (you can store indexes anywhere, e.g., in memory or in a database).
Finally, successful indexing and searching application was built using Lucene with accuracy level reached to 89% to generate relevant items on search engine. This application integrated information retrieval from unstructured documents and traditional database querying for the structured information. For the unstructured documents, AZRA system can index a variety of file formats and search in a variety of applications. By taking advantage of Lucene’s portability and scalability, our system is highly customizable. It supports a variety of keyword search queries such as wild card searches. While Lucene is a highly sophisticated search engine, it is not possible to automatically search documents using Lucene.