<p>Syftet med denna uppsats är att undersöka problem samt lösningar i relation till informationsåtervinning över språkliga gränser. Metoden som har använts i uppsatsen är studier av forskningsmaterial inom lingvistik samt främst den relativt nya forskningsdisciplinen Cross-Language Information Retrieval (CLIR). I uppsatsen hävdas att världens alla olikartade språk i dagsläget måste betraktas som ett angeläget problem för informationsvetenskapen, ty språkliga skillnader utgör ännu ett stort hinder för den internationella informationsåtervinning som tekniska framsteg, uppkomsten av Internet, digitala bibliotek, globalisering, samt stora politiska förändringar i ett flertal länder runtom i världen under de senaste åren tekniskt och teoretiskt sett har möjliggjort. I uppsatsens första del redogörs för några universellt erkända lingvistiska skillnader mellan olika språk – i detta fall främst med exempel från europeiska språk – och vanliga problem som dessa kan bidra till angående översättningar från ett språk till ett annat. I uppsatsen hävdas att dessa skillnader och problem även måste anses som relevanta när det gäller informationsåtervinning över språkliga gränser. Uppsatsen fortskrider med att ta upp ämnet Cross-Language Information Retrieval (CLIR), inom vilken lösningar på flerspråkighet och språkskillnader inom informationsåtervinning försöker utvecklas och förbättras. Målet med CLIR är att en informationssökare så småningom skall kunna söka information på sitt modersmål men ändå hitta relevant information på flera andra språk. Ett ytterligare mål är att den återfunna informationen i sin helhet även skall kunna översättas till ett för sökaren önskat språk. Fyra olika översättningsmetoder som i dagsläget finns utvecklade inom CLIR för att automatiskt kunna översätta sökfrågor, ämnesord, eller, i vissa fall, hela dokument åt en informationssökare med lite eller ingen alls kunskap om det språk som han eller hon söker information på behandlas därefter. De fyra metoderna – identifierade som maskinöversättning, tesaurus- och ordboksöversättning, korpusbaserad översättning, samt ingen översättning – diskuteras även i relation till de lingvistiska problem och skillnader som har tagits upp i uppsatsens första del. Resultatet visar att språk är någonting mycket komplext och att de olika metoderna som hittills finns utvecklade ofta kan lösa något eller några av de uppmärksammade lingvistiska översättningssvårigheterna. Dock finns det inte någon utvecklad metod som i dagsläget kan lösa samtliga problem. Uppsatsen uppmärksammar emellertid även att CLIR-forskarna i hög grad är medvetna om de nuvarande metodernas uppenbara begränsningar och att man prövar att lösa detta genom att försöka kombinera flera olika översättningsmetoder i ett CLIR-system. Avslutningsvis redogörs även för CLIR-forskarnas förväntningar och förhoppningar inför framtiden.</p> / <p>This essay deals with information retrieval across languages by examining different types of literature in the research areas of linguistics and multilingual information retrieval. The essay argues that the many different languages that co-exist around the globe must be recognised as an essential obstacle for information science. The language barrier today remains a major impediment for the expansion of international information retrieval otherwise made technically and theoretically possible over the last few years by new technical developments, the Internet, digital libraries, globalisation, and moreover many political changes in several countries around the world. The first part of the essay explores linguistic differences and difficulties related to general translations from one language to another, using examples from mainly European languages. It is suggested that these problems and differences also must be acknowledged and regarded as highly important when it comes to information retrieval across languages. The essay continues by reporting on Cross-Language Information Retrieval (CLIR), a relatively new research area where methods for multilingual information retrieval are studied and developed. The object of CLIR is that people in the future shall be able to search for information in their native tongue, but still find relevant information in more than one language. Another goal for the future is the possibility to translate complete documents into a person’s language of preference. The essay reports on four different CLIR-methods currently established for automatically translating queries, subject headings, or, in some cases, complete documents, and thus aid people with little or no knowledge of the language in which he or she is looking for information. The four methods – identified as machine translation, translations using a multilingual thesaurus or a manually produced machine readable dictionary, corpus-based translation, and no translation – are discussed in relation to the linguistic translation difficulties mentioned in the paper’s initial part. The conclusion drawn is that language is exceedingly complex and that while the different CLIR-methods currently developed often can solve one or two of the acknowledged linguistic difficulties, none is able to overcome all. The essay also show, however, that CLIR-scientists are highly aware of the limitations of the different translation methods and that many are trying to get to terms with this by incorporating several sources of translation in one single CLIR-system. The essay finally concludes by looking at CLIR-scientists’ expectations and hopes for the future.</p>

Syftet med denna uppsats är att undersöka problem samt lösningar i relation till informationsåtervinning över språkliga gränser. Metoden som har använts i uppsatsen är studier av forskningsmaterial inom lingvistik samt främst den relativt nya forskningsdisciplinen Cross-Language Information Retrieval (CLIR). I uppsatsen hävdas att världens alla olikartade språk i dagsläget måste betraktas som ett angeläget problem för informationsvetenskapen, ty språkliga skillnader utgör ännu ett stort hinder för den internationella informationsåtervinning som tekniska framsteg, uppkomsten av Internet, digitala bibliotek, globalisering, samt stora politiska förändringar i ett flertal länder runtom i världen under de senaste åren tekniskt och teoretiskt sett har möjliggjort. I uppsatsens första del redogörs för några universellt erkända lingvistiska skillnader mellan olika språk – i detta fall främst med exempel från europeiska språk – och vanliga problem som dessa kan bidra till angående översättningar från ett språk till ett annat. I uppsatsen hävdas att dessa skillnader och problem även måste anses som relevanta när det gäller informationsåtervinning över språkliga gränser. Uppsatsen fortskrider med att ta upp ämnet Cross-Language Information Retrieval (CLIR), inom vilken lösningar på flerspråkighet och språkskillnader inom informationsåtervinning försöker utvecklas och förbättras. Målet med CLIR är att en informationssökare så småningom skall kunna söka information på sitt modersmål men ändå hitta relevant information på flera andra språk. Ett ytterligare mål är att den återfunna informationen i sin helhet även skall kunna översättas till ett för sökaren önskat språk. Fyra olika översättningsmetoder som i dagsläget finns utvecklade inom CLIR för att automatiskt kunna översätta sökfrågor, ämnesord, eller, i vissa fall, hela dokument åt en informationssökare med lite eller ingen alls kunskap om det språk som han eller hon söker information på behandlas därefter. De fyra metoderna – identifierade som maskinöversättning, tesaurus- och ordboksöversättning, korpusbaserad översättning, samt ingen översättning – diskuteras även i relation till de lingvistiska problem och skillnader som har tagits upp i uppsatsens första del. Resultatet visar att språk är någonting mycket komplext och att de olika metoderna som hittills finns utvecklade ofta kan lösa något eller några av de uppmärksammade lingvistiska översättningssvårigheterna. Dock finns det inte någon utvecklad metod som i dagsläget kan lösa samtliga problem. Uppsatsen uppmärksammar emellertid även att CLIR-forskarna i hög grad är medvetna om de nuvarande metodernas uppenbara begränsningar och att man prövar att lösa detta genom att försöka kombinera flera olika översättningsmetoder i ett CLIR-system. Avslutningsvis redogörs även för CLIR-forskarnas förväntningar och förhoppningar inför framtiden. / This essay deals with information retrieval across languages by examining different types of literature in the research areas of linguistics and multilingual information retrieval. The essay argues that the many different languages that co-exist around the globe must be recognised as an essential obstacle for information science. The language barrier today remains a major impediment for the expansion of international information retrieval otherwise made technically and theoretically possible over the last few years by new technical developments, the Internet, digital libraries, globalisation, and moreover many political changes in several countries around the world. The first part of the essay explores linguistic differences and difficulties related to general translations from one language to another, using examples from mainly European languages. It is suggested that these problems and differences also must be acknowledged and regarded as highly important when it comes to information retrieval across languages. The essay continues by reporting on Cross-Language Information Retrieval (CLIR), a relatively new research area where methods for multilingual information retrieval are studied and developed. The object of CLIR is that people in the future shall be able to search for information in their native tongue, but still find relevant information in more than one language. Another goal for the future is the possibility to translate complete documents into a person’s language of preference. The essay reports on four different CLIR-methods currently established for automatically translating queries, subject headings, or, in some cases, complete documents, and thus aid people with little or no knowledge of the language in which he or she is looking for information. The four methods – identified as machine translation, translations using a multilingual thesaurus or a manually produced machine readable dictionary, corpus-based translation, and no translation – are discussed in relation to the linguistic translation difficulties mentioned in the paper’s initial part. The conclusion drawn is that language is exceedingly complex and that while the different CLIR-methods currently developed often can solve one or two of the acknowledged linguistic difficulties, none is able to overcome all. The essay also show, however, that CLIR-scientists are highly aware of the limitations of the different translation methods and that many are trying to get to terms with this by incorporating several sources of translation in one single CLIR-system. The essay finally concludes by looking at CLIR-scientists’ expectations and hopes for the future.

This Master’s thesis examines different retrieval strategies used in cross-language information retrieval (CLIR). The aim was to investigate if there were any differences between baseline queries and translated queries in retrieval effectiveness; how the retrieval effectiveness was affected by query structuring and if the results differed between different languages. The languages used in this study were Swedish, English and Finnish. 30 topics from the TrecUta collection were translated into Swedish and Finnish. Baseline queries in Swedish and Finnish were made and translated into English using a dictionary and thereby simulating automatic translation. The queries were expanded by adding all the translations from the main entries to the queries. Two kinds of queries – structured and unstructured – were designed. The queries were fed into the InQuery IR system which presented a list of retrieved documents where the relevant ones were marked. The performance of the queries was analysed by Query Performance Analyser (QPA). Average precision at seen relevant documents at DCV 10, average precision at DCV 10 and precision and recall at DCV 200 were used to measure the retrieval effectiveness. Despite the morphological differences between Swedish and Finnish, none or very small differences in retrieval performance were found, except when average precision at DCV 10 was used. The baseline queries performed the best results and the structured queries performed better in both Swedish and Finnish than the unstructured queries. The results are consistent with previous research. / Uppsatsnivå: D

Lo Wai-kit. / "October 2002." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (p. 170-184). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

A web-aided query translation expansion method in Cross-Language Information Retrieval (CLIR) is presented in this study. The method is applied to English/Chinese language pair, in which queries are expressed in English and the documents returned are in Chinese. Among the three main categories of CLIR methods of machine translation (MT), dictionary translation using a machine-readable dictionary (MRD), and parallel corpus, our method is based on the second one. MRD-based method is easy to implement. However, it faces the resource limitation problem, i.e., the dictionary is often incomplete leading to poor translation and hence undesirable results. By combining MRD and web-aided query translation expansion technique, good retrieval performance can be achieved. The performance gain is largely due to the successful translation extraction of relevant words of a query term from online texts. A new Chinese word discovery algorithm, which extracts words from continuous Chinese characters was designed and used for this purpose. The extracted relevant words do not only include the precise translation of a query term, but also those words that are relevant to that term in the source language. / Jin Honglan. / "October 2005." / Adviser: Kam Fai Wong. / Source: Dissertation Abstracts International, Volume: 67-07, Section: B, page: 3899. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (p. 115-121). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract in English and Chinese. / School code: 1307.

English-language news articles are no longer necessarily the best source of information. The Web allows information to spread more quickly and travel farther: first-person accounts of breaking news events pop up on social media, and foreign-language news articles are accessible to, if not immediately understandable by, English-speaking users. This thesis focuses on developing automatic summarization techniques for these new sources of information. We focus on summarizing two specific new sources of information: personal narratives, first-person accounts of exciting or unusual events that are readily found in blog entries and other social media posts, and non-English documents, which must first be translated into English, often introducing translation errors that complicate the summarization process. Personal narratives are a very new area of interest in natural language processing research, and they present two key challenges for summarization. First, unlike many news articles, whose lead sentences serve as summaries of the most important ideas in the articles, personal narratives provide no such shortcuts for determining where important information occurs in within them; second, personal narratives are written informally and colloquially, and unlike news articles, they are rarely edited, so they require heavier editing and rewriting during the summarization process. Non-English documents, whether news or narrative, present yet another source of difficulty on top of any challenges inherent to their genre: they must be translated into English, potentially introducing translation errors and disfluencies that must be identified and corrected during summarization. The bulk of this thesis is dedicated to addressing the challenges of summarizing personal narratives found on the Web. We develop a two-stage summarization system for personal narrative that first extracts sentences containing important content and then rewrites those sentences into summary-appropriate forms. Our content extraction system is inspired by contextualist narrative theory, using changes in writing style throughout a narrative to detect sentences containing important information; it outperforms both graph-based and neural network approaches to sentence extraction for this genre. Our paraphrasing system rewrites the extracted sentences into shorter, standalone summary sentences, learning to mimic the paraphrasing choices of human summarizers more closely than can traditional lexicon- or translation-based paraphrasing approaches. We conclude with a chapter dedicated to summarizing non-English documents written in low-resource languages – documents that would otherwise be unreadable for English-speaking users. We develop a cross-lingual summarization system that performs even heavier editing and rewriting than does our personal narrative paraphrasing system; we create and train on large amounts of synthetic errorful translations of foreign-language documents. Our approach produces fluent English summaries from disdisfluent translations of non-English documents, and it generalizes across languages.

Este trabalho propõe a utilização de algoritmos de mineração de regras de associação para a Recuperação de Informações Multilíngues. Esses algoritmos têm sido amplamente utilizados para analisar transações de registro de vendas. A ideia é mapear o problema de encontrar associações entre itens vendidos para o problema de encontrar termos equivalentes entre idiomas diferentes em um corpus paralelo. A proposta foi validada por meio de experimentos com diferentes idiomas, conjuntos de consultas e corpora. Os resultados mostram que a eficácia da abordagem proposta é comparável ao estado da arte, ao resultado monolíngue e à tradução automática de consultas, embora este utilize técnicas mais complexas de processamento de linguagem natural. Foi criado um protótipo que faz consultas à Web utilizando o método proposto. O sistema recebe palavras-chave em português, as traduz para o inglês e submete a consulta a diversos sites de busca. / This work proposes the use of algorithms for mining association rules as an approach for Cross-Language Information Retrieval. These algorithms have been widely used to analyze market basket data. The idea is to map the problem of finding associations between sales items to the problem of finding term translations over a parallel corpus. The proposal was validated by means of experiments using different languages, queries and corpora. The results show that the performance of our proposed approach is comparable to the performance of the monolingual baseline and to query translation via machine translation, even though these systems employ more complex Natural Language Processing techniques. A prototype for cross-language web querying was implemented to test the proposed method. The system accepts keywords in Portuguese, translates them into English and submits the query to several web-sites that provide search functionalities.

Este trabalho propõe a utilização de algoritmos de mineração de regras de associação para a Recuperação de Informações Multilíngues. Esses algoritmos têm sido amplamente utilizados para analisar transações de registro de vendas. A ideia é mapear o problema de encontrar associações entre itens vendidos para o problema de encontrar termos equivalentes entre idiomas diferentes em um corpus paralelo. A proposta foi validada por meio de experimentos com diferentes idiomas, conjuntos de consultas e corpora. Os resultados mostram que a eficácia da abordagem proposta é comparável ao estado da arte, ao resultado monolíngue e à tradução automática de consultas, embora este utilize técnicas mais complexas de processamento de linguagem natural. Foi criado um protótipo que faz consultas à Web utilizando o método proposto. O sistema recebe palavras-chave em português, as traduz para o inglês e submete a consulta a diversos sites de busca. / This work proposes the use of algorithms for mining association rules as an approach for Cross-Language Information Retrieval. These algorithms have been widely used to analyze market basket data. The idea is to map the problem of finding associations between sales items to the problem of finding term translations over a parallel corpus. The proposal was validated by means of experiments using different languages, queries and corpora. The results show that the performance of our proposed approach is comparable to the performance of the monolingual baseline and to query translation via machine translation, even though these systems employ more complex Natural Language Processing techniques. A prototype for cross-language web querying was implemented to test the proposed method. The system accepts keywords in Portuguese, translates them into English and submits the query to several web-sites that provide search functionalities.

Este trabalho propõe a utilização de algoritmos de mineração de regras de associação para a Recuperação de Informações Multilíngues. Esses algoritmos têm sido amplamente utilizados para analisar transações de registro de vendas. A ideia é mapear o problema de encontrar associações entre itens vendidos para o problema de encontrar termos equivalentes entre idiomas diferentes em um corpus paralelo. A proposta foi validada por meio de experimentos com diferentes idiomas, conjuntos de consultas e corpora. Os resultados mostram que a eficácia da abordagem proposta é comparável ao estado da arte, ao resultado monolíngue e à tradução automática de consultas, embora este utilize técnicas mais complexas de processamento de linguagem natural. Foi criado um protótipo que faz consultas à Web utilizando o método proposto. O sistema recebe palavras-chave em português, as traduz para o inglês e submete a consulta a diversos sites de busca. / This work proposes the use of algorithms for mining association rules as an approach for Cross-Language Information Retrieval. These algorithms have been widely used to analyze market basket data. The idea is to map the problem of finding associations between sales items to the problem of finding term translations over a parallel corpus. The proposal was validated by means of experiments using different languages, queries and corpora. The results show that the performance of our proposed approach is comparable to the performance of the monolingual baseline and to query translation via machine translation, even though these systems employ more complex Natural Language Processing techniques. A prototype for cross-language web querying was implemented to test the proposed method. The system accepts keywords in Portuguese, translates them into English and submits the query to several web-sites that provide search functionalities.

Concept maps, introduced by Novak, aid learners' understanding. I hypothesize that concept maps also can function as a summary of large documents, e.g., electronic theses and dissertations (ETDs). I have built a system that automatically generates concept maps from English-language ETDs in the computing field. The system also will provide Spanish translations of these concept maps for native Spanish speakers. Using machine translation techniques, my approach leads to concept maps that could allow researchers to discover pertinent dissertations in languages they cannot read, helping them to decide if they want a potentially relevant dissertation translated. I am using a state-of-the-art natural language processing system, called Relex, to extract noun phrases and noun-verb-noun relations from ETDs, and then produce concept maps automatically. I also have incorporated information from the table of contents of ETDs to create novel styles of concept maps. I have conducted five user studies, to evaluate user perceptions about these different map styles. I am using several methods to translate node and link text in concept maps from English to Spanish. Nodes labeled with single words from a given technical area can be translated using wordlists, but phrases in specific technical fields can be difficult to translate. Thus I have amassed a collection of about 580 Spanish-language ETDs from Scirus and two Mexican universities and I am using this corpus to mine phrase translations that I could not find otherwise. The usefulness of the automatically-generated and translated concept maps has been assessed in an experiment at Universidad de las Americas (UDLA) in Puebla, Mexico. This experiment demonstrated that concept maps can augment abstracts (translated using a standard machine translation package) in helping Spanish speaking users find ETDs of interest. / Ph. D.