RIAO ConferencePub Date : 2007-05-30DOI: 10.5555/1931390.1931439
Enrico Bragante, M. Melucci
{"title":"Homepage Finding in Hybrid Peer-to-Peer Networks","authors":"Enrico Bragante, M. Melucci","doi":"10.5555/1931390.1931439","DOIUrl":"https://doi.org/10.5555/1931390.1931439","url":null,"abstract":"This paper illustrates a ranking scheme which combines fulltext, anchor text and URL structure for homepage finding in hybrid peer-to-peer networks. The experimental results show that the proposed ranking scheme permits to find the correct homepages after exploring a small portion of a hybrid, hierarchical peer-to-peer network when the group of peers which includes the peer that stores the correct homepage is selected. A large, highly heterogeneous Web data test collection searched by homepage finding queries was used. The low computational overhead and the good effectiveness allow for an implementation in information retrieval environments.","PeriodicalId":120472,"journal":{"name":"RIAO Conference","volume":"152 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123431211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RIAO ConferencePub Date : 2007-05-30DOI: 10.5555/1931390.1931406
Ming-yu Chen, Alexander Hauptmann
{"title":"Discriminative Fields for Modeling Semantic Concepts in Video","authors":"Ming-yu Chen, Alexander Hauptmann","doi":"10.5555/1931390.1931406","DOIUrl":"https://doi.org/10.5555/1931390.1931406","url":null,"abstract":"A current trend in video analysis research hypothesizes that a very large number of semantic concepts could provide a novel way to characterize, retrieve and understand video. These semantic concepts do not appear in isolatation to each other and thus it could be very useful to exploit the relationships between multiple semantic concepts to enhance the concept detection performance in video. In this paper we present a discriminative learning framework called Multi-concept Discriminative Random Field (MDRF) for building probabilistic models of video semantic concept detectors by incorporating related concepts as well as the low-level observations. The proposed model exploits the power of discriminative graphical models to simultaneously capture the associations of concept with observed data and the interactions between related concepts. Compared with previous methods, this model not only captures the co-occurrence between concepts but also incorporates the raw data observations into a unified framework. We also present an approximate parameter estimation algorithm and apply it to the TRECVID 2005 data. Our experiments show promising results compared to the single concept learning approach for semantic concept detection in video.","PeriodicalId":120472,"journal":{"name":"RIAO Conference","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123727145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RIAO ConferencePub Date : 2007-05-30DOI: 10.5555/1931390.1931440
G. Cabanac, M. Chevalier, C. Chrisment, C. Julien
{"title":"Collective Annotation: Perspectives for Information Retrieval Improvement","authors":"G. Cabanac, M. Chevalier, C. Chrisment, C. Julien","doi":"10.5555/1931390.1931440","DOIUrl":"https://doi.org/10.5555/1931390.1931440","url":null,"abstract":"Nowadays we enter the Web 2.0 era where people's participation is a key principle. In this context, collective annotations enable to share and discuss readers' feedback with regard to digital documents. The results of this activity are going to be used in the Information Retrieval context, which already tends to harness similar collective contributions. In this paper, we propose a collective annotation model supporting feedback exchange through discussion threads. Considering this model, we associate annotations with a measure of the sparked consensus degree (social validation), this allows to provide a synthesized view of associated discussions. Finally, we investigate how Information Retrieval systems may benefit from the proposed model, thus taking advantage of human-contributed highly value-added information, namely collective annotations.","PeriodicalId":120472,"journal":{"name":"RIAO Conference","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125199697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RIAO ConferencePub Date : 2007-05-30DOI: 10.5555/1931390.1931435
Adrian Daniel Popescu
{"title":"Image Retrieval Using a Multilingual Ontology","authors":"Adrian Daniel Popescu","doi":"10.5555/1931390.1931435","DOIUrl":"https://doi.org/10.5555/1931390.1931435","url":null,"abstract":"Search engines are among the most useful Internet applications. There exist several media types on the Web and, given the particularities of each of them, adapted search solutions are required. We limit our discussion to image search engines. While rapid and robust, existing image search engines offer results that respond only partially to the user's queries. An improvement of image search results might be obtained with the introduction of semantics in the dedicated systems. Here, we discuss the construction and the utilization of a multilingual lexical resources (WordNets in several languages) to improve image retrieval on the Internet. Given the initial nouns hierarchies in the WordNets, we build a multilingual OWL ontology including knowledge in English, Italian, and Spanish. A pictured representation of a dog remains a representation of a dog in spite of the associated name (would this be dog, perro or cane). The use of a large scale multilingual ontology allows us to offer the consequent sets of responses for the concepts in the hierarchy irrespective to the initial language the query was formulated in. With the use of an ontology to structure an image database, we can solve problems related to the ambiguity of a query content and we obtain an important gain in precision in the image sets rendered to the user compared to state of the art system.","PeriodicalId":120472,"journal":{"name":"RIAO Conference","volume":"204 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115718592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RIAO ConferencePub Date : 2007-05-30DOI: 10.5555/1931390.1931423
Xing Wei, W. Bruce Croft
{"title":"Investigating Retrieval Performance with Manually-Built Topic Models","authors":"Xing Wei, W. Bruce Croft","doi":"10.5555/1931390.1931423","DOIUrl":"https://doi.org/10.5555/1931390.1931423","url":null,"abstract":"Modeling text with topics is currently a popular research area in both Machine Learning and Information Retrieval (IR). Most of this research has focused on automatic methods though there are many hand-crafted topic resources available online. In this paper we investigate retrieval performance with topic models constructed manually based on a hand-crafted directory resource. The original query is smoothed on the manually selected topic model, which can also be viewed as an \"ideal\" user context model. Experiments with these topic models on the TREC retrieval tasks show that this type of topic model alone provides little benefit, and the overall performance is not as good as relevance modeling (which is an automatic query modification model). However, smoothing the query with topic models outperforms relevance models for a subset of the queries and automatic selection from these two models for particular queries gives better results overall than relevance models. We further demonstrate some improvements over relevance models with automatically built topic models based on the directory resource.","PeriodicalId":120472,"journal":{"name":"RIAO Conference","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130342550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RIAO ConferencePub Date : 2007-05-30DOI: 10.5555/1931390.1931434
Feng Kang, Rong Jin, S. Hoi
{"title":"Similarity Beyond Distance Measurement","authors":"Feng Kang, Rong Jin, S. Hoi","doi":"10.5555/1931390.1931434","DOIUrl":"https://doi.org/10.5555/1931390.1931434","url":null,"abstract":"One of the keys issues to content-based image retrieval is the similarity measurement of images. Images are represented as points in the space of low-level visual features and most similarity measures are based on certain distance measurement between these features. Given a distance metric, two images with shorter distance are deemed to more similar than images that are far away. The well-known problem with these similarity measures is the semantic gap, namely two images separated by large distance could share the same semantic content. In this paper, we propose a novel similarity measure of images that goes beyond the distance measurement. The key idea is to exploit the clustering structure of images when a large number of images are present. The similarity of two images is determined not only by their Euclidean distance in the space of visual features but also by the likelihood for them to be clustered together, which is further estimated using a marginalized kernel. Our empirical studies with COREL datasets have shown that the proposed similarity measure is effective for traditional content-based image retrieval as well as user relevance feedback.","PeriodicalId":120472,"journal":{"name":"RIAO Conference","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128307859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RIAO ConferencePub Date : 2007-05-30DOI: 10.5555/1931390.1931437
A. Chandramouli, Susan Gauch
{"title":"A Co-operative Web Services Paradigm for Supporting Crawlers","authors":"A. Chandramouli, Susan Gauch","doi":"10.5555/1931390.1931437","DOIUrl":"https://doi.org/10.5555/1931390.1931437","url":null,"abstract":"The traditional crawlers used by search engines to build their collection of Web pages frequently gather unmodified pages that already exist in their collection. This creates unnecessary Internet traffic and wastes search engine resources during page collection and indexing. Generally, the crawlers are also unable to collect dynamic pages, causing them to miss valuable information, and they cannot easily detect deleted pages, resulting in outdated search engine collections. To address these issues, we propose a new Web services paradigm for Website/crawler interaction that is co-operative and exploits the information present in the Web logs and file system. Our system supports a querying mechanism wherein the crawler can issue queries to the Web service on the Website and then collect pages based on the information provided in response to the query. We present experimental results demonstrating that, when compared to traditional crawlers, this approach provides bandwidth savings, more complete Web page collections, and collections that are notified of deleted pages. We experimentally compare the relative merits of using only Web logs, only file system information, and combinations of the two sources to provide information for the Web service.","PeriodicalId":120472,"journal":{"name":"RIAO Conference","volume":"259 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133838225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RIAO ConferencePub Date : 2007-05-30DOI: 10.5555/1931390.1931407
Anan Liu, Jintao Li, Yongdong Zhang, Sheng Tang, Zhaoxuan Yang
{"title":"Multi-modal Interview Concept Detection for Rushes Exploitation","authors":"Anan Liu, Jintao Li, Yongdong Zhang, Sheng Tang, Zhaoxuan Yang","doi":"10.5555/1931390.1931407","DOIUrl":"https://doi.org/10.5555/1931390.1931407","url":null,"abstract":"According to the concepts of Large-Scale Concept Ontology for Multimedia (LSCOM) and requirement of the 4th task in the 2006 TRECVID, i.e., rushes exploitation, the \"interview\" concept is an important semantic concept for rushes content analysis. The paper presents the shot-level \"interview\" concept detection method. Face detection and audio classification are implemented to detect \"face\" and \"speech\" concepts for each shot. By integrating audiovisual information, \"interview\" concept is finally detected. The utilization of the method will definitely benefit the video edit. Large-scale experimental results strongly demonstrate the accuracy and effectiveness of the proposed method.","PeriodicalId":120472,"journal":{"name":"RIAO Conference","volume":"198 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133343616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RIAO ConferencePub Date : 2007-05-30DOI: 10.5555/1931390.1931430
K. Pinel-Sauvagnat, M. Boughanem
{"title":"A Survey on XML Focussed Component Retrieval","authors":"K. Pinel-Sauvagnat, M. Boughanem","doi":"10.5555/1931390.1931430","DOIUrl":"https://doi.org/10.5555/1931390.1931430","url":null,"abstract":"Focussed XML component retrieval is one of the most important challenges in the XML IR field. The aim of the focussed retrieval strategy is to find the most exhaustive and specific element in a path, i.e. to retrieve elements that focus on the user need, without nested elements. In this paper, we introduce a relevance propagation method dealing with focussed XML component retrieval. Many experiments are carried out with the INEX 2005 test suite to define what are the main characteristics of relevant elements in focussed retrieval and to compare such characteristics with those of relevant elements in thorough retrieval (where the aim is to find all relevant elements in the collection). Our main findings are the following. First, a term weighting scheme taking into account the importance of terms in elements and both in collection of elements and collection of documents is useful. Moreover, the introduction of component length as a threshold on results or used in a weighted propagation function improves significantly the results. Third, contextual relevance seems not to be useful, which contradicts results obtained by state-of-the-art methods for non-focussed retrieval. At last, the use of structural hints increases up to 50% performances we obtained when using queries composed only of simple keyword terms.","PeriodicalId":120472,"journal":{"name":"RIAO Conference","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115825138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RIAO ConferencePub Date : 2007-05-30DOI: 10.5555/1931390.1931420
M. Baziz, M. Boughanem, G. Pasi, H. Prade
{"title":"An Information Retrieval Driven by Ontology: from Query to Document Expansion","authors":"M. Baziz, M. Boughanem, G. Pasi, H. Prade","doi":"10.5555/1931390.1931420","DOIUrl":"https://doi.org/10.5555/1931390.1931420","url":null,"abstract":"The paper proposes an approach to information retrieval based on the use of a structure (ontology) both for document (resp. query) indexing and query evaluating. The conceptual structure is hierarchical and it encodes the knowledge of the topical domain of the considered documents. It is formally represented as a tree. In this approach, the query evaluation is based on the comparison of minimal sub-trees containing the two sets of nodes corresponding to the concepts expressed in the document and the query respectively. The comparison is based on the computation of a degree of inclusion of the query tree in the document tree. Experiments undertaken on MuchMore benchmark showed the effectiveness of the approach.","PeriodicalId":120472,"journal":{"name":"RIAO Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128676965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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