Literature Review of the Pioneering Approaches in Cloud-based Search Engines Powered by LETOR Techniques
It provides an incremental overview for researchers and practitioners in enterprise domains dealing with fast-growing data, but does not introduce new methods.
This literature review addresses the need for improved enterprise search by summarizing state-of-the-art technologies to enhance retrieval performance, enable cloud deployment, and optimize query expansion and suggestions.
Search engines play an essential role in our daily lives. Nonetheless, they are also very crucial in enterprise domain to access documents from various information sources. Since traditional search systems index the documents mainly by looking at the frequency of the occurring words in these documents, they are barely able to support natural language search, but rather keyword search. It seems that keyword based search will not be sufficient for enterprise data which is growing extremely fast. Thus, enterprise search becomes increasingly critical in corporate domain. In this report, we present an overview of the state-of-the-art technologies in literature for three main purposes: i) to increase the retrieval performance of a search engine, ii) to deploy a search platform to a cloud environment, and iii) to select the best terms in expanding queries for achieving even a higher retrieval performance as well as to provide good query suggestions to its users for a better user experience.