A Similarity Measure for Formal Ontologies with an application to - PowerPoint PPT Presentation

Jan 24, 2024 •432 likes •566 views

A Similarity Measure for Formal Ontologies with an application to ontologies of a geographic kind Mark Hall Midflight presentation for the master thesis 27 .01.2006 Overview I Topic Evaluation of data instance statistics Progress &

A Similarity Measure for Formal Ontologies with an application to ontologies of a geographic kind Mark Hall Midflight presentation for the master thesis 27 .01.2006
Overview I Topic Evaluation of data instance statistics Progress & Outlook Mark Hall A Similarity Measure for Formal Ontologies 27 .01.2006
What’s it all about, Basil? Problem: Semantic harmonisation of heterogeneous data sets Domain: Land-Use/Land-Cover data Solution: Semantic similarity measure based on hybrid cognitive model Mark Hall A Similarity Measure for Formal Ontologies 27 .01.2006
Overview II Topic Evaluation of data instance statistics Progress & Outlook Mark Hall A Similarity Measure for Formal Ontologies 27 .01.2006
Instance Statistics Frequency of Polygons and relative Area calculated No significant correlation found Differences in Topography Differences in Granularity of Catalogue Differences in Granularity of Data Mark Hall A Similarity Measure for Formal Ontologies 27 .01.2006
Frequency Problem Mark Hall A Similarity Measure for Formal Ontologies 27 .01.2006
Dominant Category Mark Hall A Similarity Measure for Formal Ontologies 27 .01.2006
Topographical Differences Mark Hall A Similarity Measure for Formal Ontologies 27 .01.2006
Granularity Differences Mark Hall A Similarity Measure for Formal Ontologies 27 .01.2006
Overview III Topic Evaluation of data instance statistics Progress & Outlook Mark Hall A Similarity Measure for Formal Ontologies 27 .01.2006
How’ we doin’ mate? Decent :-) 2 1/2 Chapters written Mark Hall A Similarity Measure for Formal Ontologies 27 .01.2006
Land ahoy! Still on course 1st complete version at end of February Clean up in March Mark Hall A Similarity Measure for Formal Ontologies 27 .01.2006
Thank you Q&A now Is anybody watching me?

Download Presentation

Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend

A Semantic Similarity Measure for Formal Ontologies Mark Hall Final presentation for the master

A Semantic Similarity Measure for Formal Ontologies Mark Hall Final presentation for the master thesis 17.03.2006 Overview I A Semantic Similarity Model and Algorithm Motivation - Heterogeneous Data Ontologies Similarity Measures Hybrid

493 views • 27 slides

Formal rmal Foundations oundations of of Ontologies Ontologies and and Reasoning Reasoning

Formal Ontologies Introduction to DLs Formal rmal Foundations oundations of of Ontologies Ontologies and and Reasoning Reasoning Ivan Ivan Varzinczak rzinczak Universit dArtois & CNRS, France http://www.ijv.ovh Ivan

1.3k views • 101 slides

Formal rmal Foundations oundations of of Ontologies Ontologies and and Reasoning Reasoning

Making Statements DL Knowledge Bases Entailment in DLs Formal rmal Foundations oundations of of Ontologies Ontologies and and Reasoning Reasoning Ivan Ivan Varzinczak rzinczak Universit dArtois & CNRS, France

896 views • 74 slides

Similarity Measures There are an enormous number of ways in which we can measure similarity

Similarity Measures There are an enormous number of ways in which we can measure similarity They vary depending on whether the items we are interested in analysing come from one sample or two; are qualitative or quantitative; binary,

355 views • 7 slides

Ontologies for NLP NLP for Ontologies FOIS 2014 - LogOnto Workshop on Logics and Ontologies for

Ontologies for NLP NLP for Ontologies FOIS 2014 - LogOnto Workshop on Logics and Ontologies for Natural Language Overview NLP for Ontologies Ontologies for NLP Portuguese resources Research at PUCRS Introduction We think and we

757 views • 71 slides

Choosing the Right Similarity Measure John Holliday, University of Sheffield, UK Overview

Choosing the Right Similarity Measure John Holliday, University of Sheffield, UK Overview Bias fusion of similarity coefficients Machine learning approach Design your own coefficient Fusion of fingerprint pathlengths

611 views • 33 slides

Prosopography and Computer Ontologies: towards a formal representation of the factoid

Prosopography and Computer Ontologies: towards a formal representation of the factoid model by means of CIDOC-CRM John Bradley , Michele Pasin Department of Digital Humanities, Digital Science, London, UK Kings College, London

659 views • 32 slides

Shared content-vocabularies: Ontologies Formal, machine processable explicit specification

Semantic Web Languages: RDF, RDF Schema, OWL Frank van Harmelen Vrije Universiteit Amsterdam Shared content-vocabularies: Ontologies Formal, machine processable explicit specification concepts, properties, relations, functions of a

382 views • 17 slides

Building a Cross-lingual Relatedness Thesaurus using a Graph Similarity Measure Lukas

Building a Cross-lingual Relatedness Thesaurus using a Graph Similarity Measure Lukas Michelbacher Florian Laws Beate Dorow Ulrich Heid Hinrich Sch utze Institute for Natural Language Processing University of Stuttgart

546 views • 17 slides

Time- -dependent Similarity Measure dependent Similarity Measure Time Time-dependent Similarity

Time- -dependent Similarity Measure dependent Similarity Measure Time Time-dependent Similarity Measure of Queries Using Historical Click- - of Queries Using Historical Click- of Queries Using Historical Click through Data through Data

481 views • 23 slides

A Similarity Measure for the ALN Description Logic Nicola Fanizzi, Claudia dAmato Dipartimento

A Similarity Measure for the ALN Description Logic Nicola Fanizzi, Claudia dAmato Dipartimento di Informatica Universit` a degli Studi di Bari Campus Universitario, Via Orabona 4, 70125 Bari, Italy CILC 2006 Bari Introduction &

420 views • 22 slides

The ENCOPLOT Similarity Measure for Automatic Detection of Plagiarism Cristian Grozea 1 Marius

The ENCOPLOT Similarity Measure for Automatic Detection of Plagiarism Cristian Grozea 1 Marius Nicolae Popescu 2 cristian.grozea@brainsignals.de Fraunhofer Institute FIRST Berlin University of Bucharest Romania September 23, 2011 C.Grozea,

543 views • 20 slides

Image Retargeting Shai Avidan Tel Aviv University Bidirectional Similarity (Simakov et al.

Image Retargeting Shai Avidan Tel Aviv University Bidirectional Similarity (Simakov et al. 2008) The Bidirectional (dis)similarity measure for images S and T: Goal: Given S, find T s.t. min d(S,T) Bidirectional Similarity The error

929 views • 33 slides

Semantic Similarity MultiJEDI ERC 259234 Semantic Similarity Semantic Similarity Mostly

SemEval 2014 Task-3 Cross-Level Semantic Similarity MultiJEDI ERC 259234 Semantic Similarity Semantic Similarity Mostly focused on similar types of lexical items Semantic Similarity What if we have different types of inputs? CLSS:

971 views • 47 slides

Linking Families with Enriched Ontologies David W. Embley (FamilySearch), Stephen W. Liddle (BYU),

Linking Families with Enriched Ontologies David W. Embley (FamilySearch), Stephen W. Liddle (BYU), Deryle W. Lonsdale (BYU), Scott N. Woodfield (BYU & FamilySearch) Linking Families Enriched Ontologies An ontology is a formal, explicit

492 views • 14 slides

How to Select an Compared Values . . . Appropriate Similarity Case When No Scaling . . . Case

Practitioners . . . Limitations of Correlation Other Similarity Measures How to Select a . . . How to Select an Compared Values . . . Appropriate Similarity Case When No Scaling . . . Case When All . . . Measure: Towards a Case When Only .

356 views • 22 slides

DEVELOPMENT BUG PREVENTION AND ISOLATION Erika Dignam and Ross Cunniff 04 April 2016 ABOUT US

April 4-7, 2016 | Silicon Valley ROBUST SOFTWARE DEVELOPMENT BUG PREVENTION AND ISOLATION Erika Dignam and Ross Cunniff 04 April 2016 ABOUT US Ross Cunniff Senior Software Engineer and NVIDIA SPEC representative. 15-year NVIDIA employee.

550 views • 44 slides

Density-Based Clustering over an Evolving Data Stream with Noise Feng Cao Martin Ester

Density-Based Clustering over an Evolving Data Stream with Noise Feng Cao Martin Ester Weining Qian Aoying Zhou Abstract into meaningful classes. The data stream for mining often exists over months or years, and the underlying

134 views • 12 slides

This circular consists of two annexes: (1) Annex 1 is the guidelines for the presentation of

C C S Technical Information (2020) Technical Information No.8 Total No.442 Jan.16,2020 (Total 2 pages) To: Relevant shipowners, ship management companies, shipyards and designers, product manufacturer, related departments of the Headquarters of

518 views • 35 slides

Trekking through the Trees: Forest Succession at the Trinity River Audubon Center Jewel Lipps

Trekking through the Trees: Forest Succession at the Trinity River Audubon Center Jewel Lipps Southern Methodist University Dallas, TX Trinity River Corridor Project, Jan. 15 http://www.trinityrivercorridor.com/maps/TRC-project-map.pdf

365 views • 12 slides

Deep Learning for Predictive Maintenance Pawel Morkisz GTC 2017 Agenda Problem

Deep Learning for Predictive Maintenance Pawel Morkisz GTC 2017 Agenda Problem Introduction and notion of deep neural networks o Convolutional layers o Residual networks (ResNet) One dimensional convolutional networks in failure

276 views • 23 slides

A Renewable E nergy Strategy for the Republic of Cyprus and the Potential Contribution from the

Dimitrios Nikolaidis & Stephen R. Smith Department of civil & environmental engineering, Imperial College London A Renewable E nergy Strategy for the Republic of Cyprus and the Potential Contribution from the Solid Waste Management

265 views • 22 slides

Brief Overview What Is PaveXpress? Overview of the AASHTO Design Guide Page-by-Page

3/7/2016 A Simplified Pavement Design Tool 36 th Annual WV Asphalt Paving Asphalt Paving Conference Danny Gierhart, P.E. Regional Engineer Asphalt Institute www.PaveXpressDesign.com Brief Overview What Is PaveXpress? Overview of the

513 views • 38 slides

More on the Reliability Function of the BSC Alexander Barg Andrew McGregor DIMACS, Rutgers

More on the Reliability Function of the BSC Alexander Barg Andrew McGregor DIMACS, Rutgers University University of Pennsylvania ISIT 2003, Yokohama Some Definitions Some Definitions Communicating over a binary symmetric channel with

941 views • 48 slides