4,439 research outputs found
Dublin City University at CLEF 2004: experiments with the ImageCLEF St Andrew's collection
For the CLEF 2004 ImageCLEF St Andrew's Collection task
the Dublin City University group carried out three sets of experiments: standard cross-language information retrieval (CLIR) runs using topic translation via machine translation (MT), combination of this run with image matching results from the VIPER system, and a novel document rescoring approach based on automatic MT evaluation metrics. Our standard MT-based CLIR works well on this task. Encouragingly combination with image matching lists is also observed to produce small positive changes in the retrieval output. However, rescoring using the MT evaluation metrics in their current form significantly reduced retrieval
effectiveness
Exploiting Query Structure and Document Structure to Improve Document Retrieval Effectiveness
In this paper we present a systematic analysis of document
retrieval using unstructured and structured queries within
the score region algebra (SRA) structured retrieval framework. The behavior of di®erent retrieval models, namely
Boolean, tf.idf, GPX, language models, and Okapi, is tested
using the transparent SRA framework in our three-level structured retrieval system called TIJAH. The retrieval models are implemented along four elementary retrieval aspects: element and term selection, element score computation, score combination, and score propagation.
The analysis is performed on a numerous experiments
evaluated on TREC and CLEF collections, using manually
generated unstructured and structured queries. Unstructured queries range from the short title queries to long title
+ description + narrative queries. For generating structured
queries we exploit the knowledge of the document structure
and the content used to semantically describe or classify
documents. We show that such structured information can
be utilized in retrieval engines to give more precise answers to user queries then when using unstructured queries
PRES: A score metric for evaluating recall-oriented information retrieval applications
Information retrieval (IR) evaluation scores are generally
designed to measure the effectiveness with which relevant
documents are identified and retrieved. Many scores have been proposed for this purpose over the years. These have primarily focused on aspects of precision and recall, and while these are often discussed with equal importance, in practice most attention has been given to precision focused metrics. Even for recalloriented IR tasks of growing importance, such as patent retrieval, these precision based scores remain the primary evaluation measures. Our study examines different evaluation measures for a recall-oriented patent retrieval task and demonstrates the limitations of the current scores in comparing different IR systems for this task. We introduce PRES, a novel evaluation metric for this type of application taking account of recall and the user’s search effort. The behaviour of PRES is demonstrated on 48 runs from the CLEF-IP 2009 patent retrieval track. A full analysis of the performance of PRES shows its suitability for measuring the
retrieval effectiveness of systems from a recall focused
perspective taking into account the user’s expected search effort
Searching and organizing images across languages
With the continual growth of users on the Web
from a wide range of countries, supporting
such users in their search of cultural heritage
collections will grow in importance. In the
next few years, the growth areas of Internet
users will come from the Indian sub-continent
and China. Consequently, if holders of cultural
heritage collections wish their content to be
viewable by the full range of users coming to
the Internet, the range of languages that they
need to support will have to grow. This paper
will present recent work conducted at the
University of Sheffield (and now being
implemented in BRICKS) on how to use
automatic translation to provide search and
organisation facilities for a historical image
search engine. The system allows users to
search for images in seven different languages,
providing means for the user to examine
translated image captions and browse retrieved
images organised by categories written in their
native language
CLEF 2005: Ad Hoc track overview
We describe the objectives and organization of the CLEF 2005 ad hoc track and discuss the main characteristics of the tasks offered to test monolingual, bilingual and multilingual textual document retrieval. The performance achieved for each task is presented and a preliminary analysis of results is given. The paper focuses in particular on the multilingual tasks which reused the test collection created in CLEF 2003 in an attempt to see if an improvement in system performance over time could be measured, and also to examine the multilingual results merging problem
GeoCLEF 2007: the CLEF 2007 cross-language geographic information retrieval track overview
GeoCLEF ran as a regular track for the second time within the Cross
Language Evaluation Forum (CLEF) 2007. The purpose of GeoCLEF is to test
and evaluate cross-language geographic information retrieval (GIR): retrieval
for topics with a geographic specification. GeoCLEF 2007 consisted of two sub
tasks. A search task ran for the third time and a query classification task was
organized for the first. For the GeoCLEF 2007 search task, twenty-five search
topics were defined by the organizing groups for searching English, German,
Portuguese and Spanish document collections. All topics were translated into
English, Indonesian, Portuguese, Spanish and German. Several topics in 2007
were geographically challenging. Thirteen groups submitted 108 runs. The
groups used a variety of approaches. For the classification task, a query log
from a search engine was provided and the groups needed to identify the
queries with a geographic scope and the geographic components within the
local queries
User experiments with the Eurovision cross-language image retrieval system
In this paper we present Eurovision, a text-based system for cross-language (CL) image retrieval.
The system is evaluated by multilingual users for two search tasks with the system configured in
English and five other languages. To our knowledge this is the first published set of user
experiments for CL image retrieval. We show that: (1) it is possible to create a usable multilingual
search engine using little knowledge of any language other than English, (2) categorizing images
assists the user's search, and (3) there are differences in the way users search between the proposed
search tasks. Based on the two search tasks and user feedback, we describe important aspects of
any CL image retrieval system
GeoCLEF 2006: the CLEF 2006 Ccross-language geographic information retrieval track overview
After being a pilot track in 2005, GeoCLEF advanced to be a regular track within CLEF 2006. The
purpose of GeoCLEF is to test and evaluate cross-language geographic information retrieval (GIR): retrieval for
topics with a geographic specification. For GeoCLEF 2006, twenty-five search topics were defined by the
organizing groups for searching English, German, Portuguese and Spanish document collections. Topics were
translated into English, German, Portuguese, Spanish and Japanese. Several topics in 2006 were significantly
more geographically challenging than in 2005. Seventeen groups submitted 149 runs (up from eleven groups and
117 runs in GeoCLEF 2005). The groups used a variety of approaches, including geographic bounding boxes,
named entity extraction and external knowledge bases (geographic thesauri and ontologies and gazetteers)
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
An evaluation of Bradfordizing effects
The purpose of this paper is to apply and evaluate the bibliometric method Bradfordizing for information retrieval (IR) experiments. Bradfordizing is used for generating core document sets for subject-specific questions and to reorder result sets from distributed searches. The method will be applied and tested in a controlled scenario of scientific literature databases from social and political sciences, economics, psychology and medical science (SOLIS, SoLit, USB Köln Opac, CSA Sociological Abstracts, World Affairs Online, Psyndex and Medline) and 164 standardized topics. An evaluation of the method and its effects is carried out in two laboratory-based information retrieval experiments (CLEF and KoMoHe) using a controlled document corpus and human relevance assessments. The results show that Bradfordizing is a very robust method for re-ranking the main document types (journal articles and monographs) in today’s digital libraries (DL). The IR tests show that relevance distributions after re-ranking improve at a significant level if articles in the core are compared with articles in the succeeding zones. The items in the core are significantly more often assessed as relevant, than items in zone 2 (z2) or zone 3 (z3). The improvements between the zones are statistically significant based on the Wilcoxon signed-rank test and the paired T-Test
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