131 research outputs found
Conceptualizations of the Cataloging Object: A Critique on Current Perceptions of FRBR Group 1 Entities
No full textLibraries face a double challenge in the digital age: both the describing framework and the describing object are under change. FRBR attempts to generate a coherent theory and yield a new Paradigm of cataloging. This study deploys current conceptualizations of the FRBR Group 1 entities within the FRBR models family with a view to semantic interoperability. FRBR cannot be considered as simple metadata describing a specific resource but more like some kind of knowledge related to the resource. This study reveals that there are different perspectives of what is introduced by FRBR as the cataloging object in the context of various interpretations of the model, namely RDA, FRBRization projects and FRBROO
Libraries’ metadata as data in the era of the Semantic Web: Modeling a repository of Master theses and PhD dissertations for the Web of Data
No full textThis study argues that metadata of library catalogs can stand autonomously, providing valuable information detached from the resources they point to and, therefore, could be used as data in the context of the Semantic Web. We present an analysis of this perception followed by an implementation proposal for a Master's thesis and PhD dissertation repository. The analysis builds on the flexibility of the Resource Description Framework (RDF) and takes into account the Functional Requirements for Bibliographic Records (FRBR) and Functional Requirements for Authority Data (FRAD) in order to reveal the latent academic network by linking its entities to a meaningful and computationally processable set. Current library catalogs retrieve documents to find answers, whereas in our approach catalogs can provide answers that could not be found in any specific document
In the Name of the Name : RDF Literals, ER Attributes, and the Potential to Rethink the Structures and Visualizations of Catalogs
No full textThe aim of this study is to contribute to the field of machine-processable bibliographic data that is suitable for the Semantic Web. We examine the Entity Relationship (ER) model, which has been selected by IFLA as a “conceptual framework” in order to model the FR family (FRBR, FRAD, and RDA), and the problems ER causes as we move towards the Semantic Web. Subsequently, while maintaining the semantics of the aforementioned standards but rejecting the ER as a conceptual framework for bibliographic data, this paper builds on the RDF (Resource Description Framework) potential and documents how both the RDF and Linked Data’s rationale can affect the way we model bibliographic data.
In this way, a new approach to bibliographic data emerges where the distinction between description and authorities is obsolete. Instead, the integration of the authorities with descriptive information becomes fundamental so that a network of correlations can be established between the entities and the names by which the entities are known. Naming is a vital issue for human cultures because names are not random sequences of characters or sounds that stand just as identifiers for the entities—they also have socio-cultural meanings and interpretations. Thus, instead of describing indivisible resources, we could describe entities that appear in a variety of names on various resources. In this study, a method is proposed to connect the names with the entities they represent and, in this way, to document the provenance of these names by connecting specific resources with specific names
Aircraft Marshaling Signals Dataset of FMCW Radar and Event-Based Camera for Sensor Fusion
No full textDataset Introduction
The advent of neural networks capable of learning salient features from variance in the radar data has expanded the breadth of radar applications, often as an alternative sensor or a complementary modality to camera vision. Gesture recognition for command control is the most commonly explored application. Nevertheless, more suitable benchmarking datasets are needed to assess and compare the merits of the different proposed solutions. Furthermore, most current publicly available radar datasets used in gesture recognition provide little diversity, do not provide access to raw ADC data, and are not significantly challenging. To address these shortcomings, we created and made available a new dataset that combines two synchronized modalities: radar and dynamic vision camera of 10 aircraft marshalling signals at several distances and angles, recorded from 13 people. Moreover, we propose a sparse encoding of the time domain (ADC) signals that achieve a dramatic data rate reduction (>76%) while retaining the efficacy of the downstream FFT processing (<2% accuracy loss on recognition tasks). Finally, we demonstrate early sensor fusion results based on compressed radar data encoding in range-Doppler maps with dynamic vision data. This approach achieves higher accuracy than either modality alone.
Dataset Structure
The dataset has a common directory structure which contains additional information about the captures.
dataset_dir///--/ofxRadar8Ghz_yyyy-mm-dd_HH-MM-SS.rad
Identifiers
stage [train, test].
room: [conference_room, foyer, open_space].
person: [0-9]. Note that 0 stands for no person, and 1 for an unlabeled, random person (only present in test).
gesture: ['none', 'emergency_stop', 'move_ahead', 'move_back_v1', 'move_back_v2', 'slow_down' 'start_engines', 'stop_engines', 'straight_ahead', 'turn_left', 'turn_right'].
distance: ['xxx', '100', '150', '200', '250', '300', '350', '400', '450'] (in cm). Note that xxx is used for none gestures when there is no person present in front of the radar (i.e. background samples), or when a person is walking infront of the radar with varying distances but performing no gesture.If you use this dataset, please also cite our accompanying paper:
@inproceedings{mueller2023aircraft, title={Aircraft Marshalling Signals Dataset of Radar and Event-Based Camera for Sensor Fusion}, author={M\"uller, Leon and Sifalakis, Manolis and Eissa, Sherif and Yousefzadeh, Amirreza and Detterer, Paul and Stuijk, Sander, and Corradi, Federico}, journal={IEEE Radar Conference, San Antonio, TX}, volume={}, number={1}, pages={1--15}, year={2023}, publisher={IEE}
Query Expansion of Zero-Hit Subject Searches: Using a Thesaurus in Conjunction with NLP Techniques
No full textThe focus of our study is zero-hit queries in keyword subject searches and the effort of increasing recall in these cases by reformulating and, then, expanding the initial queries using an external source of knowledge, namely a thesaurus. To this end, the objectives of this study are twofold. First, we perform the mapping of query terms to the thesaurus terms. Second, we use the matched terms to expand the user’s initial query by taking advantage of the thesaurus relations and implementing natural language processing (NLP) techniques. We report on the overall procedure and elaborate on key points and considerations of each step of the process
Loose ends: almost one in five human genes still have unresolved coding status
No full textThe authors have accidently omitted one co-author. Part of the work described in this study was performed in the laboratory of Dr Manolis Kellis, Computer Science and Electrical Engineering Department, Massachusetts Institute of Technology, Cambridge, MA, USA and The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Dr Kellis’ name has been added to the authorship and the published article has been updated
FRBRization: using UNIMARC link fields to identify Works
No full textThe main objective of this study is to amalgamate the MARC 21 FRBRization practices with UNIMARC format semantics and to highlight some differences between them in the context of FRBRization. The main focus is to examine the possibility of using the UNIMARC link fields in order to identify the Functional Requirements for Bibliographic Records (FRBR) Work entities. In our approach we suggest that all records linked with 45X fields may belong to the same Work with the record which contains these fields. As a test set of this approach we used a sample of records of ancient Greek authors from the Union Catalogue of Hellenic
Academic Libraries
SKOS Concepts and Natural Language Concepts: an Analysis of Latent Relationships in KOSs
No full textThe vehicle to represent Knowledge Organisation Systems (KOSs) in the environment of the Semantic Web and linked data is the Simple Knowledge Organisation System (SKOS). SKOS provides a way to assign a Uniform Resource Identifier (URI) to each concept, and this URI functions as a surrogate for the concept. This fact makes of main concern the need to clarify the URIs’ ontological meaning. The aim of this study is to investigate the relationship between the ontological substance of KOS concepts and concepts revealed through the grammatical and syntactic formalisms of natural language. For this purpose, we examined the dividableness of concepts in specific KOSs (i.e. a thesaurus, a subject headings system and a classification scheme) by applying Natural Language Processing (NLP) techniques (i.e. morphosyntactic analysis) to the lexical representations (i.e. RDF literals) of SKOS concepts. The results of the comparative analysis reveal that, despite the use of multi-word units, thesauri tend to represent concepts in a way that can hardly be further divided conceptually, while subject headings and classification schemes – to a certain extent – comprise terms that can be decomposed into more conceptual constituents. Consequently, SKOS concepts deriving from thesauri are more likely to represent atomic conceptual units and thus be more appropriate tools for inference and reasoning. Since identifiers represent the meaning of a concept, complex concepts are neither the most appropriate nor the most efficient way of modelling a KOS for the Semantic Web
The linked data ecosystem for SSH and a case study from the cultural heritage domain
No full textSemantic Web, an extension of the current web, focuses on the structure of data. The aim is to develop data structures that will be more effectively processable by computers, in contrast to the limited functionality of the contemporary scriptocentric web. Semantic Web, therefore, aims to transform the web into a global ‘database’ and lead the developments toward the Web of Data. The specifications developed or related to this aim, as well as the processes and rules for achieving it, are known as Linked Data, i.e. (inter)connected data from different sources. Linked Data creates a content-agnostic, as well as software-agnostic ecosystem, which can be used for encoding and publishing all types of information from various domains.
The first presentation of this webinar introduces the basic concepts of Linked Data and shows that Linked Data are particularly suitable for Social Sciences and Humanities (SSH) since they do not emphasize metrics and quantifications but conceptualizations and reason. After presenting the paradigm shift introduced by linked data concerning the development of the web, a case study from the cultural heritage domain will be discussed.
The second presentation showcases SearchCulture.gr, the Greek cross-domain Cultural Data Aggregator, as a state-of-the-art case, for the use of Linked data in the cultural domain. The National Documentation Centre of Greece (EKT) develops this service, which has collected a growing number of 800.000 digitized Cultural Heritage Objects (CHOs) from 73 cultural institutions. Moreover, it is the Accredited National Aggregator for Europeana having provided more than 580.000 CHOs so far. Addressing metadata heterogeneity has been a key target from the start. Controlled Linked Data vocabularies for item types, historical periods, subjects and persons have been developed over the course of the past years and are being used for the semantic enrichment of the CHOs’ metadata. This presentation addresses the challenges, methodology and tools used over the past 7 years for the process of enriching the aggregated CHOs’ metadata. This process classifies and disambiguates the aggregated data, provides multilinguality and adds significant browse and search functionalities to the portal and, therefore, opens new horizons for SSH research
Cognitive abstraction approach to sketch-based image retrieval
No full textThesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.Includes bibliographical references (leaves 151-157).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.As digital media become more popular, corporations and individuals gather an increasingly large number of digital images. As a collection grows to more than a few hundred images, the need for search becomes crucial. This thesis is addressing the problem of retrieving from a small database a particular image previously seen by the user. This thesis combines current findings in cognitive science with the knowledge of previous image retrieval systems to present a novel approach to content based image retrieval and indexing. We focus on algorithms which abstract away information from images in the same terms that a viewer abstracts information from an image. The focus in Imagina is on the matching of regions, instead of the matching of global measures. Multiple representations, focusing on shape and color, are used for every region. The matches of individual regions are combined using a saliency metric that accounts for differences in the distributions of metrics. Region matching along with configuration determines the overall match between a query and an image.by Manolis Kamvysselis and Ovidiu Marina.S.B.and M.Eng
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