A Survey of Designing Multilingual Document Retrieval and Ranking in Cloud

A Survey of Multilingual Text Retrieval

This report reviews the present state of the art in selection of texts in one language based on queries in another a problem we refer to as multilingual text retrieval Present applications of multilingual text retrieval systems are limited by the cost and complexity of developing and using the multilingual thesauri on which they are based and by the level of user training that is required to ac...

A Complete Survey on Web Document Ranking

Today, web plays a critical role in human life and also simplifies the same to a great extent. However, due to the towering increase in the number of web pages, the challenge of providing quality and relevant information to the users also needs to be addressed. Thus, search engines need to implement such algorithms which spans the pages as per user's interest and satisfaction and rank them...

Semi-supervised ranking for document retrieval

Ranking functions are an important component of information retrieval systems. Recently there has been a surge of research in the field of “learning to rank”, which aims at using labeled training data and machine learning algorithms to construct reliable ranking functions. Machine learning methods such as neural networks, support vector machines, and least squares have been successfully applied...

Chinese Document Retrieval at Trec-6 1 Multilingual Document Retrieval in Trec

The TREC-6 conference was the fourth year in which document retrieval in a language other than English was carried out. In TREC-3, 4 groups participated in an ad hoc retrieval task on a collection of 208 Mbytes of Mexican newspaper text in the Spanish language. In TREC-4 there were 10 groups who participated, once again in an ad hoc document retrieval task on the same Mexican newspaper texts bu...

Survey: Multilingual Text Retrieval and Access