MIRACLE Retrieval Experiments with East Asian Languages

This paper describes the participation of MIRACLE in NTCIR 2005 CLIR task. Although our group has a strong background and long expertise in Computational Linguistics and Information Retrieval applied to European languages and using Latin and Cyrillic alphabets, this was our first attempt on East Asian languages. Our main goal was to study the particularities and distinctive characteristics of Japanese, Chinese and Korean, specially focusing on the similarities and differences with European languages, and carry out research on CLIR tasks which include those languages. The basic idea behind our participation in NTCIR is to test if the same familiar linguisticbased techniques may also applicable to East Asian languages, and study the necessary adaptations

Which User Interaction for Cross-Language Information Retrieval? Design Issues and Reflections

A novel and complex form of information access is cross-language information retrieval: searching for texts written in foreign languages based on native language queries. Although the underlying technology for achieving such a search is relatively well understood, the appropriate interface design is not. This paper presents three user evaluations undertaken during the iterative design of Clarity, a cross-language retrieval system for rare languages, and shows how the user interaction design evolved depending on the results of usability tests. The first test was instrumental to identify weaknesses in both functionalities and interface; the second was run to determine if query translation should be shown or not; the final was a global assessment and focussed on user satisfaction criteria. Lessons were learned at every stage of the process leading to a much more informed view of what a cross-language retrieval system should offer to users

Which User Interaction for Cross-Language Information Retrieval? Design Issues and Reflections

A novel and complex form of information access is cross-language information retrieval: searching for texts written in foreign languages based on native language queries. Although the underlying technology for achieving such a search is relatively well understood, the appropriate interface design is not. This paper presents three user evaluations undertaken during the iterative design of Clarity, a cross-language retrieval system for rare languages, and shows how the user interaction design evolved depending on the results of usability tests. The first test was instrumental to identify weaknesses in both functionalities and interface; the second was run to determine if query translation should be shown or not; the final was a global assessment and focussed on user satisfaction criteria. Lessons were learned at every stage of the process leading to a much more informed view of what a cross-language retrieval system should offer to users

Which user interaction for cross-language information retrieval? Design issues and reflections

A novel and complex form of information access is cross-language information retrieval: searching for texts written in foreign languages based on native language queries. Although the underlying technology for achieving such a search is relatively well understood, the appropriate interface design is not. The authors present three user evaluations undertaken during the iterative design of Clarity, a cross-language retrieval system for low-density languages, and shows how the user-interaction design evolved depending on the results of usability tests. The first test was instrumental to identify weaknesses in both functionalities and interface; the second was run to determine if query translation should be shown or not; the final was a global assessment and focused on user satisfaction criteria. Lessons were learned at every stage of the process leading to a much more informed view of what a cross-language retrieval system should offer to users

DCU's experiments in NTCIR-8 IR4QA task

We describe DCU's participation in the NTCIR-8 IR4QA task [16]. This task is a cross-language information retrieval(CLIR) task from English to Simplified Chinese which seeks to provide relevant documents for later cross language question answering (CLQA) tasks. For the IR4QA task, we submitted 5 official runs including two monolingual runs and three CLIR runs. For the monolingual retrieval we tested two information retrieval models. The results show that the KL-Divergence language model method performs better than the Okapi BM25 model for the Simplified Chinese retrieval task. This agrees with our previous CLIR experimental results at NTCIR-5. For the CLIR task, we compare query translation and document translation methods. In the query translation based runs, we tested a method for query expansion from external resource (QEE) before query translation. Our result for this run is slightly lower than the run without QEE. Our results show that the document translation method achieves 68.24% MAP performance compared to our best query translation run. For the document translation method, we found that the main issue is the lack of named entity translation in the documents since we do not have a suitable parallel corpus for training data for the statistical machine translation system. Our best CLIR run comes from the combination of query translation using Google translate and the KL-Divergence language model retrieval method. It achieves 79.94% MAP relative to our best monolingual run

Toward higher effectiveness for recall-oriented information retrieval: A patent retrieval case study

Research in information retrieval (IR) has largely been directed towards tasks requiring high precision. Recently, other IR applications which can be described as recall-oriented IR tasks have received increased attention in the IR research domain. Prominent among these IR applications are patent search and legal search, where users are typically ready to check hundreds or possibly thousands of documents in order to find any possible relevant document. The main concerns in this kind of application are very different from those in standard precision-oriented IR tasks, where users tend to be focused on finding an answer to their information need that can typically be addressed by one or two relevant documents. For precision-oriented tasks, mean average precision continues to be used as the primary evaluation metric for almost all IR applications. For recall-oriented IR applications the nature of the search task, including objectives, users, queries, and document collections, is different from that of standard precision-oriented search tasks. In this research study, two dimensions in IR are explored for the recall-oriented patent search task. The study includes IR system evaluation and multilingual IR for patent search. In each of these dimensions, current IR techniques are studied and novel techniques developed especially for this kind of recall-oriented IR application are proposed and investigated experimentally in the context of patent retrieval. The techniques developed in this thesis provide a significant contribution toward evaluating the effectiveness of recall-oriented IR in general and particularly patent search, and improving the efficiency of multilingual search for this kind of task

Cross-language Information Retrieval

Two key assumptions shape the usual view of ranked retrieval: (1) that the searcher can choose words for their query that might appear in the documents that they wish to see, and (2) that ranking retrieved documents will suffice because the searcher will be able to recognize those which they wished to find. When the documents to be searched are in a language not known by the searcher, neither assumption is true. In such cases, Cross-Language Information Retrieval (CLIR) is needed. This chapter reviews the state of the art for CLIR and outlines some open research questions.Comment: 49 pages, 0 figure

Evaluating Information Retrieval and Access Tasks

This open access book summarizes the first two decades of the NII Testbeds and Community for Information access Research (NTCIR). NTCIR is a series of evaluation forums run by a global team of researchers and hosted by the National Institute of Informatics (NII), Japan. The book is unique in that it discusses not just what was done at NTCIR, but also how it was done and the impact it has achieved. For example, in some chapters the reader sees the early seeds of what eventually grew to be the search engines that provide access to content on the World Wide Web, today’s smartphones that can tailor what they show to the needs of their owners, and the smart speakers that enrich our lives at home and on the move. We also get glimpses into how new search engines can be built for mathematical formulae, or for the digital record of a lived human life. Key to the success of the NTCIR endeavor was early recognition that information access research is an empirical discipline and that evaluation therefore lay at the core of the enterprise. Evaluation is thus at the heart of each chapter in this book. They show, for example, how the recognition that some documents are more important than others has shaped thinking about evaluation design. The thirty-three contributors to this volume speak for the many hundreds of researchers from dozens of countries around the world who together shaped NTCIR as organizers and participants. This book is suitable for researchers, practitioners, and students—anyone who wants to learn about past and present evaluation efforts in information retrieval, information access, and natural language processing, as well as those who want to participate in an evaluation task or even to design and organize one