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Current Search:
All of 'Information' and 'retrieval' in all fields;
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Displaying Results 26 - 50 of 1077 on page 2 of 44
Marked
Mark
Adaptive systems for multimedia information retrieval
(2004)
Jones, Gareth J.F.
Adaptive systems for multimedia information retrieval
(2004)
Jones, Gareth J.F.
Abstract:
Multimedia information retrieval poses both technical and design challenges beyond those of established text retrieval. These issues extend both to the entry of search requests, system interation and the browsing of retrieved content, and the methodologies and techniques for content indexing. Prototype multimedia information retrieval systems are currently being developed which enable the exploration of both the user interaction and technical issues. The suitability of the solutions developed within these systems is currently being explored in the annual TRECVID evaluation workshops which enable researchers to test their indexing and retrieval algorithms and complete systems on common tasks and datasets.
http://doras.dcu.ie/16264/
Marked
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Query performance prediction for information retrieval based on covering topic score
(2008)
Lang, Hao ; Wang, Bin ; Jones, Gareth J.F.; Li, Jintao ; Ding, Fan ; Liu, Yi-Xuan
Query performance prediction for information retrieval based on covering topic score
(2008)
Lang, Hao ; Wang, Bin ; Jones, Gareth J.F.; Li, Jintao ; Ding, Fan ; Liu, Yi-Xuan
Abstract:
We present a statistical method called Covering Topic Score (CTS) to predict query performance for information retrieval. Estimation is based on how well the topic of a user's query is covered by documents retrieved from a certain retrieval system. Our approach is conceptually simple and intuitive, and can be easily extended to incorporate features beyond bag-of-words such as phrases and proximity of terms. Experiments demonstrate that CTS significantly correlates with query performance in a variety of TREC test collections, and in particular CTS gains more prediction power benefiting from features of phrases and proximity of terms. We compare CTS with previous state-of-the-art methods for query performance prediction including clarity score and robustness score. Our experimental results show that CTS consistently performs better than, or at least as well as, these other methods. In addition to its high effectiveness, CTS is also shown to have very low computational complexity,...
http://doras.dcu.ie/16507/
Marked
Mark
The application of morpho-syntatic language processing to effective information retrieval
(1991)
Sheridan, Páraic
The application of morpho-syntatic language processing to effective information retrieval
(1991)
Sheridan, Páraic
Abstract:
The fundamental function of an information retrieval system is to retrieve texts or documents from a database in response to a user’s request for information, such that the content of the retreived documents will be relevant to the user’s original information need. This is accomplished through matching the user’s information request against the texts in the database in order to estimate which texts are relevant. In this thesis I propose a method for using current natural language processing techniques for the construction of a text representation to be used in an information retrieval system. In order to support this proposal I have designed a matching algorithm specifically for performing the retrieval task of matching user queries against texts in a database, using the proposed text representation. Having designed this text representation and matching algorithm, I then constructed an experiment to investigate the effectiveness of the algorithm at matching phrases. This experiment...
http://doras.dcu.ie/19419/
Marked
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Towards Multilingual User Models for Personalized Multilingual Information Retrieval
(2011)
GHORAB, MOHAMMED RAMI ELHUSSEIN; ZHOU, DONG; STEICHEN, BEN; WADE, VINCENT PATRICK
Towards Multilingual User Models for Personalized Multilingual Information Retrieval
(2011)
GHORAB, MOHAMMED RAMI ELHUSSEIN; ZHOU, DONG; STEICHEN, BEN; WADE, VINCENT PATRICK
Abstract:
The majority of studies in Personalized Information Retrieval (PIR) literature have focused on monolingual IR, and only relatively little work has been done concerning multilingual IR. In this paper we propose a novel method to represent user models in a multilingual fashion. We argue that such representation would be more suitable for Personalized Multilingual Information Retrieval (PMIR). Furthermore, we outline two algorithms for query adaptation based on user information from the multilingual user model.
http://hdl.handle.net/2262/63759
Marked
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Utilizing recommender algorithms for enhanced information retrieval
(2013)
Li, Wei B.; Jones, Gareth J.F.
Utilizing recommender algorithms for enhanced information retrieval
(2013)
Li, Wei B.; Jones, Gareth J.F.
Abstract:
Retrieving relevant items which meet a user’s information need is the key objective of information retrieval (IR). Current IR systems generally seek to satisfy search queries independently without considering search history information from other searchers. By contrast, algorithms used in recommender systems (RSs) are designed to predict the future popularity of an item by aggregating ratings of the reactions of previous users of an item. This observation motivates us to explore the application of RS methods in IR to increase search effectiveness. In this study, we examine the suitability of recommender algorithms (RAs) for use in IR applications and methods for combining RAs into IR systems by fusing their respective outputs. A novel RA is proposed to enhance the RS performance in our integrated application. Experimental results are reported for an extended version of the FIRE 2011 personalized IR data collection. Noticeably better results are obtained using our approach.
http://doras.dcu.ie/20367/
Marked
Mark
Integrating methods from IR and QA for geographic information retrieval
(2009)
Leveling, Johannes; Hartrumpf, Sven
Integrating methods from IR and QA for geographic information retrieval
(2009)
Leveling, Johannes; Hartrumpf, Sven
Abstract:
This paper describes the participation of GIRSA at Geo- CLEF 2008, the geographic information retrieval task at CLEF. GIRSA combines information retrieval (IR) on geographically annotated data and question answering (QA) employing query decomposition. For the monolingual German experiments, several parameter settings were varied: using a single index or separate indexes for content and geographic annotation, using complex term weighting, adding location names from the topic narrative, and merging results from IR and QA, which yields the highest mean average precision (0.2608 MAP). For bilingual experiments, English and Portuguese topics were translated via the web services Applied Language Solutions, Google Translate, and Promt Online Translator. For both source languages, Google Translate seems to return the best translations. For English (Portuguese) topics, 60.2% (80.0%) of the maximum MAP for monolingual German experiments, or 0.1571 MAP (0.2085 MAP), is achieved. As a post-ocia...
http://doras.dcu.ie/16444/
Marked
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NLP-SIR: A Natural Language Approach for Spreadsheet Information Retrieval
(2001)
Flood, Derek; McDaid, Kevin; McCaffery, Fergal
NLP-SIR: A Natural Language Approach for Spreadsheet Information Retrieval
(2001)
Flood, Derek; McDaid, Kevin; McCaffery, Fergal
Abstract:
Spreadsheets are a ubiquitous software tool, used for a wide variety of tasks such as financial modelling, statistical analysis and inventory management. Extracting meaningful information from such data can be a difficult task, especially for novice users unfamiliar with the advanced data processing features of many spreadsheet applications. We believe that through the use of Natural Language Processing (NLP) techniques this task can be made considerably easier. This paper introduces NLP-SIR, a Natural language interface for spreadsheet information retrieval. The results of a recent evaluation which compared NLP-SIR with existing Information retrieval tools are also outlined. This evaluation has shown that NLP-SIR is a more effective method of spreadsheet information retrieval.
http://eprints.dkit.ie/112/
Marked
Mark
A Framework for the Evaluation of Adaptive IR Systems through Implicit Recommendation
(2011)
O'DONNELL, EILEEN; LAWLESS, SEAMUS; GHORAB, MOHAMMED RAMI ELHUSSEIN; WADE, VINCENT...
A Framework for the Evaluation of Adaptive IR Systems through Implicit Recommendation
(2011)
O'DONNELL, EILEEN; LAWLESS, SEAMUS; GHORAB, MOHAMMED RAMI ELHUSSEIN; WADE, VINCENT; SHARP, MARY; MULWA, CATHERINE
Abstract:
Personalised Information Retrieval (PIR) has gained considerable attention in recent literature. In PIR different stages of the retrieval process are adapted to the user, such as adapting the user?s query or the results. Personalised recommender frameworks are endowed with intelligent mechanisms to search for products, goods and services that users are interested in. The objective of such tools is to evaluate and filter the huge amount of information available within a specific scope to assist users in their information access processes. This paper presents a web-based adaptive framework for evaluating personalised information retrieval systems. The framework uses implicit recommendation to guide users in deciding which evaluation techniques, metrics and criteria to use. A task-based experiment was conducted to test the functionality and performance of the framework. A Review of evaluation techniques for personalised IR systems was conducted and the results of the analysed survey ar...
http://hdl.handle.net/2262/62487
Marked
Mark
A comparative survey of Personalised Information Retrieval and Adaptive Hypermedia techniques
(2012)
STEICHEN, BEN; ASHMAN, HELEN; WADE, VINCENT PATRICK
A comparative survey of Personalised Information Retrieval and Adaptive Hypermedia techniques
(2012)
STEICHEN, BEN; ASHMAN, HELEN; WADE, VINCENT PATRICK
Abstract:
A key driver for next generation web information retrieval systems is becoming the degree to which a user?s search and presentation experience is adapted to individual user properties and contexts of use. Over the past decades, two parallel threads of personalisation research have emerged, one originating in the document space in the area of Personalised Information Retrieval (PIR) and the other arising from the hypertext space in the field of Adaptive Hypermedia (AH). PIR typically aims to bias search results towards more personally relevant information by modifying traditional document ranking algorithms. Such techniques tend to represent users with simplified personas (often based on historic interests), enabling the efficient calculation of personalised ranked lists. On the other hand, the field of Adaptive Hypermedia (AH) has addressed the challenge of biasing content retrieval and presentation by adapting towards multiple characteristics. These characteristics, more typically...
http://hdl.handle.net/2262/63741
Marked
Mark
CIKM 2013 workshop on living labs for information retrieval evaluation
(2013)
Balog, Krisztian; Elsweiler, David; Kanoulas, Evangelos; Kelly, Liadh; Smucker, Mark
CIKM 2013 workshop on living labs for information retrieval evaluation
(2013)
Balog, Krisztian; Elsweiler, David; Kanoulas, Evangelos; Kelly, Liadh; Smucker, Mark
Abstract:
In the past few years the information retrieval (IR) community has been exploring ways to move further away from the Cranfield style evaluation paradigm, and make evaluations more ‘realistic’ (more centered on real users, their needs and behaviours). As part of this drive, living labs which involve and integrate users in the research process have been proposed. The Living Labs for Information Retrieval Evaluation workshop (LL’13) brings together for the first time people interested in progressing the living labs for IR evaluation methodology.
http://doras.dcu.ie/20118/
Marked
Mark
Creation of a new evaluation benchmark for information retrieval targeting patient information needs
(2013)
Goeuriot, Lorraine; Kelly, Liadh; Jones, Gareth J.F.; Zuccon, Guido; Suominen, Hanna; H...
Creation of a new evaluation benchmark for information retrieval targeting patient information needs
(2013)
Goeuriot, Lorraine; Kelly, Liadh; Jones, Gareth J.F.; Zuccon, Guido; Suominen, Hanna; Hanbury, Allan; Mueller, Henning; Leveling, Johannes
Abstract:
Searching for health advice on the web is becoming increasingly common. Because of the great importance of this activity for patients and clinicians and the effect that incorrect information may have on health outcomes, it is critical to present relevant and valuable information to a searcher. Previous evaluation campaigns on health information retrieval (IR) have provided benchmarks that have been widely used to improve health IR and record these improvements. However, in general these benchmarks have targeted the specialised information needs of physicians and other healthcare workers. In this paper, we describe the development of a new collection for evaluation of effectiveness in IR seeking to satisfy the health information needs of patients. Our methodology features a novel way to create statements of patients’ information needs using realistic short queries associated with patient discharge summaries, which provide details of patient disorders. We adopt a scenario where the pa...
http://doras.dcu.ie/20123/
Marked
Mark
Adapting binary information retrieval evaluation metrics for segment-based retrieval tasks
(2013)
Aly, Robin; Eskevich, Maria; Ordelman, Roeland; Jones, Gareth J.F.
Adapting binary information retrieval evaluation metrics for segment-based retrieval tasks
(2013)
Aly, Robin; Eskevich, Maria; Ordelman, Roeland; Jones, Gareth J.F.
Abstract:
This report describes metrics for the evaluation of the effectiveness of segment-based retrieval based on existing binary information retrieval metrics. This metrics are described in the context of a task for the hyperlinking of video segments. This evaluation approach re-uses existing evaluation measures from the standard Cranfield evaluation paradigm. Our adaptation approach can in principle be used with any kind of effectiveness measure that uses binary relevance, and for other segment-baed retrieval tasks. In our video hyperlinking setting, we use precision at a cut-off rank n and mean average precision.
http://doras.dcu.ie/20377/
Marked
Mark
Information access for personal media archives
(2010)
Doherty, Aiden R.; Gurrin, Cathal; Jones, Gareth J.F.; Smeaton, Alan F.
Information access for personal media archives
(2010)
Doherty, Aiden R.; Gurrin, Cathal; Jones, Gareth J.F.; Smeaton, Alan F.
Abstract:
It is now possible to archive much of our life experiences in digital form using a variety of sources, e.g. blogs written, tweets made, photographs taken, etc. Information can be captured from a myriad of personal information devices. In this workshop, researchers from diverse disciplines discussed how we can advance towards the goal of effective capture, retrieval and exploration of e-memories. Proposed solutions included advanced textile sensors to capture new data, P2P methods to store this data, and personal reflection applications to review this data. Much discussion centered around search and navigation strategies, interactive interfaces, and the cognitive basis in using digitally captured information as memorabilia.
http://doras.dcu.ie/15421/
Marked
Mark
A proposal for the evaluation of adaptive information retrieval systems using simulated interaction
(2010)
Mulwa, Catherine; Li, Wei B.; Lawless, Séamus; Jones, Gareth J.F.
A proposal for the evaluation of adaptive information retrieval systems using simulated interaction
(2010)
Mulwa, Catherine; Li, Wei B.; Lawless, Séamus; Jones, Gareth J.F.
Abstract:
The Centre for Next Generation Localisation (CNGL) is involved in building interactive adaptive systems which combine Information Retrieval (IR), Adaptive Hypermedia (AH) and adaptive web techniques and technologies. The complex functionality of these systems coupled with the variety of potential users means that the experiments necessary to evaluate such systems are difficult to plan, implement and execute. This evaluation requires both component-level scientific evaluation and user-based evaluation. Automated replication of experiments and simulation of user interaction would be hugely beneficial in the evaluation of adaptive information retrieval systems (AIRS). This paper proposes a methodology for the evaluation of AIRS which leverages simulated interaction. The hybrid approach detailed combines: (i) user-centred methods for simulating interaction and personalisation; (ii) evaluation metrics that combine Human Computer Interaction (HCI), AH and IR techniques; and (iii) the use ...
http://doras.dcu.ie/15837/
Marked
Mark
Notes from the ISMIR 2012 late-breaking session on evaluation in music information retrieval
(2012)
Peeters, Geoffroy; Urbano, Julian; Jones, Gareth J.F.
Notes from the ISMIR 2012 late-breaking session on evaluation in music information retrieval
(2012)
Peeters, Geoffroy; Urbano, Julian; Jones, Gareth J.F.
Abstract:
During the last day of the ISMIR 2012 conference there were two events related to Music IR Evaluation. A panel took place during the morning to discuss several issues concerning the various evaluation initiatives with the general audience at ISMIR. A late-breaking session during the afternoon kept the discussion alive between a group of researchers who wanted to dig deeper into these issues. This extended abstract reports the main topics covered during this short session and the general thoughts that came up.
http://doras.dcu.ie/17921/
Marked
Mark
Test collections for medical information retrieval evaluation
(2013)
Goeuriot, Lorraine; Kelly, Liadh; Jones, Gareth J.F.
Test collections for medical information retrieval evaluation
(2013)
Goeuriot, Lorraine; Kelly, Liadh; Jones, Gareth J.F.
Abstract:
The web has rapidly become one of the main resources for medical information for many people: patients, clinicians, medical doctors, etc. Measuring the effectiveness with which information can be retrieved from web resources for these users is crucial: it brings better information to professionals for better diagnosis, treatment, patient care; and helps patients and relatives get informed on their condition. Several existing information retrieval (IR) evaluation campaigns have been developed to assess and improve medical IR methods, for example the TREC Medical Record Track [11] and TREC Genomics Track [10]. These campaigns only target certain type of users, mainly clinicians and some medical professionals: queries are mainly centered on cohorts of records describing a specific patient cases or on biomedical reports. Evaluating search effectiveness over the many heterogeneous online medical information sources now available, which are increasingly used by a diverse range of medical ...
http://doras.dcu.ie/20122/
Marked
Mark
Enhanced information retrieval by exploiting recommender techniques in cluster-based link analysis
(2013)
Li, Wei B.; Jones, Gareth J.F.
Enhanced information retrieval by exploiting recommender techniques in cluster-based link analysis
(2013)
Li, Wei B.; Jones, Gareth J.F.
Abstract:
Inspired by the use of PageRank algorithms in document ranking, we develop and evaluate a cluster-based PageRank algorithm to re-rank information retrieval (IR) output with the objective of improving ad hoc search effectiveness. Unlike existing work, our methods exploit recommender techniques to extract the correlation between documents and apply detected correlations in a cluster-based PageRank algorithm to compute the importance of each document in a dataset. In this study two popular recommender techniques are examined in four proposed PageRank models to investigate the effectiveness of our approach. Comparison of our methods with strong baselines demonstrates the solid performance of our approach. Experimental results are reported on an extended version of the FIRE 2011 personal information retrieval (PIR) data collection which includes topically related queries with click-through data and relevance assessment data collected from the query creators. The search logs of the query ...
http://doras.dcu.ie/20373/
Marked
Mark
TRECVID: benchmarking the effectiveness of information retrieval tasks on digital video
(2003)
Smeaton, Alan F.; Over, Paul
TRECVID: benchmarking the effectiveness of information retrieval tasks on digital video
(2003)
Smeaton, Alan F.; Over, Paul
Abstract:
Many research groups worldwide are now investigating techniques which can support information retrieval on archives of digital video and as groups move on to implement these techniques they inevitably try to evaluate the performance of their techniques in practical situations. The difficulty with doing this is that there is no test collection or any environment in which the effectiveness of video IR or video IR sub-tasks, can be evaluated and compared. The annual series of TREC exercises has, for over a decade, been benchmarking the effectiveness of systems in carrying out various information retrieval tasks on text and audio and has contributed to a huge improvement in many of these. Two years ago, a track was introduced which covers shot boundary detection, feature extraction and searching through archives of digital video. In this paper we present a summary of the activities in the TREC Video track in 2002 where 17 teams from across the world took part.
http://doras.dcu.ie/278/
Marked
Mark
Video information retrieval using objects and ostensive relevance feedback
(2004)
Browne, Paul
Video information retrieval using objects and ostensive relevance feedback
(2004)
Browne, Paul
Abstract:
In this paper, we present a brief overview of current approaches to video information retrieval (IR) and we highlight its limitations and drawbacks in terms of satisfying user needs. We then describe a method of incorporating object-based relevance feedback into video IR which we believe opens up new possibilities for helping users find information in video archives. Following this we describe our own work on shot retrieval from video archives which uses object detection, object-based relevance feedback and a variation of relevance feedback called ostensive RF which is particularly appropriate for this type of retrieval.
http://doras.dcu.ie/367/
Marked
Mark
Information retrieval challenges of maintaining a context-aware human digital memory
(2008)
Gurrin, Cathal
Information retrieval challenges of maintaining a context-aware human digital memory
(2008)
Gurrin, Cathal
Abstract:
The volume of personal digital data captured from today's content creation devices, such as digital cameras, digital video recorders and sensecams pose many challenges for organising and retrieving content for users. By utilising content and contextual analysis along with an understanding of the usage scenarios involved, it is possible to develop effective information retrieval technologies for these personal archives. In this talk I will discuss how we, at the Centre for Digital Video Processing, Dublin City University, have employed both content and contextual analysis to automatically organise human digital memory (sensecam) collections and I will focus specifically on how we have employed techniques from photo and video retrieval in the novel domain of human digital memories.
http://doras.dcu.ie/662/
Marked
Mark
Utilizing sub-topical structure of documents for information retrieval.
(2011)
Ganguly, Debasis; Leveling, Johannes; Jones, Gareth J.F.
Utilizing sub-topical structure of documents for information retrieval.
(2011)
Ganguly, Debasis; Leveling, Johannes; Jones, Gareth J.F.
Abstract:
Text segmentation in natural language processing typically refers to the process of decomposing a document into constituent subtopics. Our work centers on the application of text segmentation techniques within information retrieval (IR) tasks. For example, for scoring a document by combining the retrieval scores of its constituent segments, exploiting the proximity of query terms in documents for ad-hoc search, and for question answering (QA), where retrieved passages from multiple documents are aggregated and presented as a single document to a searcher. Feedback in ad hoc IR task is shown to benefit from the use of extracted sentences instead of terms from the pseudo relevant documents for query expansion. Retrieval effectiveness for patent prior art search task is enhanced by applying text segmentation to the patent queries. Another aspect of our work involves augmenting text segmentation techniques to produce segments which are more readable with less unresolved anaphora. This is...
http://doras.dcu.ie/16518/
Marked
Mark
Adaptation of machine translation for multilingual information retrieval in the medical domain
(2014)
Pecina, Pavel; Dušek, Ondřej; Goeuriot, Lorraine; Hajič, Jan; Hlaváčová, Jaroslava; Jon...
Adaptation of machine translation for multilingual information retrieval in the medical domain
(2014)
Pecina, Pavel; Dušek, Ondřej; Goeuriot, Lorraine; Hajič, Jan; Hlaváčová, Jaroslava; Jones, Gareth J.F.; Kelly, Liadh; Leveling, Johannes; Mareček, David; Novák, Michal; Popel, Martin; Rosa, Rudolf; Tamchyna, Aleš; Urešová, Zdeňka
Abstract:
Objective. We investigate machine translation (MT) of user search queries in the context of cross-lingual information retrieval (IR) in the medical domain. The main focus is on techniques to adapt MT to increase translation quality; however, we also explore MT adaptation to improve eectiveness of cross-lingual IR. Methods and Data. Our MT system is Moses, a state-of-the-art phrase-based statistical machine translation system. The IR system is based on the BM25 retrieval model implemented in the Lucene search engine. The MT techniques employed in this work include in-domain training and tuning, intelligent training data selection, optimization of phrase table configuration, compound splitting, and exploiting synonyms as translation variants. The IR methods include morphological normalization and using multiple translation variants for query expansion. The experiments are performed and thoroughly evaluated on three language pairs: Czech–English, German–English, and French–English. MT ...
http://doras.dcu.ie/20117/
Marked
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ShARe/CLEF eHealth evaluation lab 2014, task 3: user-centred health information retrieval
(2014)
Goeuriot, Lorraine; Kelly, Liadh; Li, Wei B.; Palotti, Joao; Zuccon, Guido; Hanbury, Al...
ShARe/CLEF eHealth evaluation lab 2014, task 3: user-centred health information retrieval
(2014)
Goeuriot, Lorraine; Kelly, Liadh; Li, Wei B.; Palotti, Joao; Zuccon, Guido; Hanbury, Allan; Jones, Gareth J.F.; Mueller, Henning
Abstract:
This paper presents the results of task 3 of the ShARe/CLEF eHealth Evaluation Lab 2014. This evaluation lab focuses on improving access to medical information on the web. The task objective was to investigate the eect of using additional information such as a related discharge summary and external resources such as medical ontologies on the eectiveness of information retrieval systems, in a monolingual (Task 3a) and in a multilingual (Task 3b) context. The participants were allowed to submit up to seven runs for each language (English, Czech, French, German), one mandatory run using no additional information or external resources, and three each using or not using discharge summaries.
http://doras.dcu.ie/20110/
Marked
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DCU@FIRE-2014: an information retrieval approach for source code plagiarism detection
(2014)
Ganguly, Debasis; Jones, Gareth J.F.
DCU@FIRE-2014: an information retrieval approach for source code plagiarism detection
(2014)
Ganguly, Debasis; Jones, Gareth J.F.
Abstract:
This paper investigates an information retrieval (IR) based approach for source code plagiarism detection. The method of extensively checking pairwise similarities between documents is not scalable for large collections of source code documents. To make the task of source code plagiarism detection fast and scalable in practice, we propose an IR based approach in which each document is treated as a pseudo-query in order to retrieve a list of potential candidate documents in a decreasing order of their similarity values. A threshold is then applied on the relative similarity decrement ratios to report a set of documents as potential cases of source-code reuse. Instead of treating a source code as an unstructured text document, we explore term extraction from the annotated parse tree of a source code and also make use of field based language model for indexing and retrieval of source code documents. Results conrm that source code parsing plays a vital role in improving the plagiarism p...
http://doras.dcu.ie/20382/
Marked
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A comparative study of online translation services for cross language Information retrieval
(2015)
Hosseinzadeh Vahid, Ali; Arora, Piyush; Liu, Qun; Jones, Gareth J.F.
A comparative study of online translation services for cross language Information retrieval
(2015)
Hosseinzadeh Vahid, Ali; Arora, Piyush; Liu, Qun; Jones, Gareth J.F.
Abstract:
Technical advances and its increasing availability, mean that Machine Translation (MT) is now widely used for the translation of search queries in multilingual search tasks. A number of free-to-use high-quality online MT systems are now available and, although imperfect in their translation behaviour, are found to produce good performance in CrossLanguage Information Retrieval (CLIR) applications. Users of these MT systems in CLIR tasks generally assume that they all behave similarly in CLIR applications, and the choice of MT system is often made on the basis of convenience. We present a set of experiments which compare the impact of applying two of the best known online systems, Google and Bing translation, for query translation across multiple language pairs and for two very different CLIR tasks. Our experiments show that the MT systems perform differently on average for different tasks and language pairs, but more significantly for different individual queries. We examine the dif...
http://doras.dcu.ie/22796/
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