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  • Advancing Ontology Alignment:New Methods for Biomedical Ontology Alignment

    using Non Equivalence Relations

    by

    Suzette Kruger Stoutenburg

    B.Sc., Rowan State University, 1985

    M.Sc., National Technological University, 1989

    A dissertation submitted to the Graduate Faculty of the

    University of Colorado at Colorado Springs

    in partial fulfillment of the requirements for the degree of

    Doctor of Philosophy

    Department of Computer Science

    2009

  • cCopyright By Suzette Kruger Stoutenburg 2009All Rights Reserved

    iii

  • This dissertation forDoctor of Philosophy Degree by

    Suzette Kruger Stoutenburg

    has been approved for theDepartment of Computer Science

    by

    Dr. Jugal Kalita, Chair

    Dr. Marijke F. Augusteijn

    Dr. Terrance Boult

    Dr. Lisa Hines

    Dr. Leo Obrst

    Dr. Sudhanshu K. Semwal

    Dr. Rex Welshon

    Dr. Xiaobo Zhou

    Date

  • Stoutenburg, Suzette Kruger (Ph.D. in Engineering, Focus in Computer Science)

    Advancing Ontology Alignment: New Methods for Biomedical Ontology Alignment

    using Non Equivalence Relations

    Thesis directed by Professor Jugal K. Kalita

    Increasingly, ontologies are being developed and exposed on the Web to support

    a variety of applications, including biological knowledge sharing, enhanced search and

    discovery, and decision support. This proliferation of new Web knowledge sources is

    resulting in a growing need for integration and enrichment of these sources. Auto-

    mated and semi-automated solutions to aligning ontologies are emerging that address

    this growing need with very promising results. However, nearly all approaches have

    focused on aligning ontologies using relationships of similarity and equivalence and

    none have applied knowledge in upper ontologies. None to our knowledge have ap-

    plied Support Vector Machine (SVM) technology. Only very recently, solutions for

    scalability of ontology alignment have begun to emerge.

    The goal of this research is to advance the state of the art in automated ontol-

    ogy alignment by contributing in three main areas. First, we present new algorithms

    to extend the information can be derived in ontology alignment; specifically, new

    relationships between ontological components beyond similarity and equivalence. In

    particular, we present algorithms to align ontologies using subclass, superclass and

    relations contained within the original ontologies. We show how ontology alignment

    can be modeled in a Support Vector Machine and that use of SVMs enhances the on-

    tology alignment process. Second, we contribute new evidence for ontology alignment.

    v

  • We show that the use of semantics in conjunction with upper ontologies and other

    linguistic resources can enhance the alignment process and specifically contribute to

    the discovery of new relationships cross-ontology. Finally, we investigate scalability

    issues in the area of processing, reasoning, and aligning large-scale ontologies. We

    present an alignment algorithm that bounds processing by selecting optimal subtrees

    to align and show that this significantly improves efficiency without major reduction

    in precision.

    vi

  • To my husband and best friend, Greg

    To my parents, Mildred and the late Karl Kruger

    vii

  • Acknowledgments

    What a relief and thrill to be finally writing this section! This has been a long

    journey and it is great to finally arrive.

    First, I would like extend a special thanks to my advisor, Dr. Jugal Kalita, for

    his outstanding support and guidance throughout this process. His technical depth,

    enthusiasm and drive kept me going. Dr. Kalita gave me great freedom to pursue

    areas of interest to me and yet also provided a wealth of ideas on how to improve

    the approach. I might add that it was also a pleasure to watch his daughter Ananya

    grow before my eyes, from a baby into an adorable child, as we met week after week

    to review the research.

    I would like to acknowledge and thank my committee members for their ideas,

    support and guidance: Dr. Marijke F. Augusteijn, Dr. Terrance Boult, Dr. Lisa

    Hines, Dr. Sudhanshu K. Semwal, Dr. Rex Welshon and Dr. Xiaobo Zhou. Multiple

    exchanges with these outstanding educators enhanced the quality of the research and

    enriched my experience along the way. Ms. Patricia Rea also deserves a special

    thanks, as she was always very responsive and supportive throughout the process.

    A special thanks is extended to Dr. Lisa Hines and Kaily Ewing for their support

    and collaboration in developing reference alignments for evaluation of alignment in

    the biomedical domain. Dr. Hines and Ms. Ewing also provided expertise and

    ideas for how to apply this research in the future in the biomedical domain. Their

    expertise was invaluable to this work. I would like to thank Justin Gray for choosing

    to do his Masters thesis in ontology alignment. His software engineering expertise

    viii

  • and contributions contributed to this research early on in the process. I would also

    like to thank the members of Dr. Kalitas study group, including Jeremy Witmer,

    Justin Gray, Michael Bankston, Beaux Shariff, Mona Habib and others. Their ideas

    and support at our weekly meetings were very helpful to this research. I also thank

    Melissa Garner for her invaluable help in advanced statistics.

    I want to acknowledge the MITRE Corporation for offering me this tremendous

    opportunity. For many years, MITRE has remained one of Fortunes 100 Best Com-

    panies to Work For, in part, because of the corporations commitment to education. I

    remain honored to be part of such an outstanding organization. Special thanks go to

    my colleagues at MITRE for their support and encouragement during this four year

    process. There are too many to mention and I dont want to leave anyone out. There

    were many times when my colleagues had to fill in for me, taking on significant extra

    work during my absences. I greatly appreciate all that they did to help me succeed

    in this endeavor and I am forever in their debt. In addition, I received continuous

    support from ontology and alignment experts across MITRE. Their expertise and

    willingness to help is also greatly appreciated.

    I would like to extend a special thanks to my colleague, friend and research

    mentor, Dr. Leo Obrst. Leo was the original inspiration for my taking on this mid-

    life challenge. Leo and I collaborated together on a research proposal in 2004; soon

    after, I started this Ph.D. program with the initial goal of being able to follow Leos

    technical discussions in the areas of logic and semantics. I believe I may have achieved

    that goal and so much more, thanks to Leos encouragement and unending willingness

    to share his expertise and spend time educating others.

    ix

  • I would also like to thank my mother and dear friend, Mildred and my late father

    Karl. Without their unconditional love and support, I would not have been equipped

    to take on this challenge. They taught me to be a strong, independent woman and

    that education was the path to success and freedom. My mom also deserves special

    thanks for always being there to help us and for putting up with my long absences,

    particularly in the last few months of the dissertation preparation.

    Finally, I would like to thank my husband Greg for his unwavering support

    and encouragement during this time. Greg served as my IT support, psychologist

    and confidant. He fixed internet outages, debugged network problems and configured

    Virtual Machines with a moments notice and never a complaint. He gave me endless

    encouragement during tough times, late nights and 90+ hour weeks. He made sure

    we were stocked with light bulbs and caffeine sources, not to mention batteries for the

    wireless mouse and keyboard, especially in the final weeks of writing. His dedication

    to me and our family kept operations in our home moving (not only IT, but grocery

    shopping, bill paying, dog washing, cooking, vacuuming, etc.) and his belief in me

    was my primary inspiration. His patience with me and ability to make me laugh when

    all seems lost is legendary. We truly share in this accomplishment.

    x

  • Table of Contents

    List of Tables xv

    List of Figures xvii

    1 Introduction 1

    1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

    1.2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

    1.3 Summary of Research Goals and Contributions . . . . . . . . . . . . 7

    1.4 Research Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . 9

    1.5 Organization of Dissertation . . . . . . . . . . . . . . . . . . . . . . . 11

    2 Definitions 13

    2.1 Ontology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

    2.2 Representation of Ontologies . . . . . . . . . . . . . . . . . . . . . . . 17

    2.3 Ontology Alignment . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

    2.4 Relationships in Ontology Alignment . . . . . . . . . . . . . . . . . . 23

    2.5 The Process of Ontology Alignment . . . . . . . . . . . . . . . . . . . 25

    3 State of the Art in Ontology Alignment 28

    3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

    3.2 Alignment Techniques over Schemas . . . . . . . . . . . . . . . . . . . 29

    3.3 Alignment

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