Cross Language Information Retrieval (CLIR): A Survey of Approaches for Exploring Web Across Languages

In the era of globalization, internet being accessible and affordable has gained huge popularity and is widely being used almost everywhere by Government, private organizations, companies, banks, etc. as well as by individuals. It has empowered its users to contribute to the creation of information on web enabling them to use their native languages which consequently has drastically increased the volume of web-accessible documents available in languages other than English. This exponential growth of information on the internet has also induced several challenges before the information retrieval systems. Most of the present monolingual information retrieval systems can retrieve documents in the language of query only, missing the information in other languages that may be more relevant to the user. The need of information retrieval systems to become multilingual has given rise to the research in Cross Language Information Retrieval (CLIR) which can cross the language barriers and retrieve more relevant results from documents in different languages. This article is a review of motivation, issues, work and challenges related to various CLIR approaches. Starting with the most fundamental approaches of translation, it is attempted to study and present a review of more advanced approaches for enhancing the retrieval results in CLIR proposed by various researchers working in this domain.

Reductive and generative approaches to management of morphological variation of keywords in monolingual information retrieval

PurposeThe purpose of this article is to discuss advantages and disadvantages of various means to manage morphological variation of keywords in monolingual information retrieval.Design/methodology/approachThe authors present a compilation of query results from 11 mostly European languages and a new general classification of the language dependent techniques for management of morphological variation. Variants of the different techniques are compared in some detail in terms of retrieval effectiveness and other criteria. The paper consists mainly of an overview of different management methods for keyword variation in information retrieval. Typical IR retrieval results of 11 languages and a new classification for keyword management methods are also presented.FindingsThe main results of the paper are an overall comparison of reductive and generative keyword management methods in terms of retrieval effectiveness and other broader criteria.Originality/valueThe paper is of value to anyone who wants to get an overall picture of keyword management techniques used in IR.