5,595 research outputs found
Natural language processing
Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems
PRIME: A System for Multi-lingual Patent Retrieval
Given the growing number of patents filed in multiple countries, users are
interested in retrieving patents across languages. We propose a multi-lingual
patent retrieval system, which translates a user query into the target
language, searches a multilingual database for patents relevant to the query,
and improves the browsing efficiency by way of machine translation and
clustering. Our system also extracts new translations from patent families
consisting of comparable patents, to enhance the translation dictionary
A Cross-media Retrieval System for Lecture Videos
We propose a cross-media lecture-on-demand system, in which users can
selectively view specific segments of lecture videos by submitting text
queries. Users can easily formulate queries by using the textbook associated
with a target lecture, even if they cannot come up with effective keywords. Our
system extracts the audio track from a target lecture video, generates a
transcription by large vocabulary continuous speech recognition, and produces a
text index. Experimental results showed that by adapting speech recognition to
the topic of the lecture, the recognition accuracy increased and the retrieval
accuracy was comparable with that obtained by human transcription
Japanese/English Cross-Language Information Retrieval: Exploration of Query Translation and Transliteration
Cross-language information retrieval (CLIR), where queries and documents are
in different languages, has of late become one of the major topics within the
information retrieval community. This paper proposes a Japanese/English CLIR
system, where we combine a query translation and retrieval modules. We
currently target the retrieval of technical documents, and therefore the
performance of our system is highly dependent on the quality of the translation
of technical terms. However, the technical term translation is still
problematic in that technical terms are often compound words, and thus new
terms are progressively created by combining existing base words. In addition,
Japanese often represents loanwords based on its special phonogram.
Consequently, existing dictionaries find it difficult to achieve sufficient
coverage. To counter the first problem, we produce a Japanese/English
dictionary for base words, and translate compound words on a word-by-word
basis. We also use a probabilistic method to resolve translation ambiguity. For
the second problem, we use a transliteration method, which corresponds words
unlisted in the base word dictionary to their phonetic equivalents in the
target language. We evaluate our system using a test collection for CLIR, and
show that both the compound word translation and transliteration methods
improve the system performance
CRL at Ntcir2
We have developed systems of two types for NTCIR2. One is an enhenced version
of the system we developed for NTCIR1 and IREX. It submitted retrieval results
for JJ and CC tasks. A variety of parameters were tried with the system. It
used such characteristics of newspapers as locational information in the CC
tasks. The system got good results for both of the tasks. The other system is a
portable system which avoids free parameters as much as possible. The system
submitted retrieval results for JJ, JE, EE, EJ, and CC tasks. The system
automatically determined the number of top documents and the weight of the
original query used in automatic-feedback retrieval. It also determined
relevant terms quite robustly. For EJ and JE tasks, it used document expansion
to augment the initial queries. It achieved good results, except on the CC
tasks.Comment: 11 pages. Computation and Language. This paper describes our results
of information retrieval in the NTCIR2 contes
Automatic indexing and retrieval as a tool to improve information and technology transfer
During the last 20 years, linguistic data processing mainly has been seen as a tool to develop linguistic regularities (or detect irregularities) of a given natural language, especially to handle large textual databases ("Corpora"). A second motivation to use a computer was to test some theories or models of a language system (or a part of it) using a simulation program. As a result of both strategies, the "Saarbrücken Text Analysis System" has been implemented. At present, a very large lexical database is available to analyse written German texts morphologically and syntactically. The syntactic parser is able to handle every German sentence with more than 90% "correct" results. On the other hand, the development of large (textual) databases within different fields (e.g. law, patent specifications, medicine) is increasing rapidly. Therefore, a computer aided indexing system ("Computergestützte Texterschließung: CTX") has been developed at Regensburg and Saarbrücken University to improve the (even natural language oriented) access to textual data ("free text") applying linguistic strategies to information retrieval processes.
Main results of feasibility studies, especially in the field of German Patent Documentation, are presented
- …