Chreston Miller | Virginia Tech (original) (raw)
Papers by Chreston Miller
Journal of eScience Librarianship
Objective: An area of research in which open science may have particularly high impact is in deep... more Objective: An area of research in which open science may have particularly high impact is in deep learning (DL), where researchers have developed many algorithms to solve challenging problems, but others may have difficulty in replicating results and applying these algorithms. In response, some researchers have begun to open up DL research by making their resources available (e.g., code, datasets and/or pre-trained models) to the research community. This article describes three case studies in DL where openly available resources are used and we investigate the impact on the projects, the outcomes, and make recommendations for what to focus on when making DL resources available.Methods: Each case study represents a single project using openly available DL resources for a research project. The process and progress of each case study is recorded along with aspects such as approaches taken, documentation of openly available resources, and researchers' experience with the openly avai...
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In this paper we present the findings of three longitudinal case studies in which a new method fo... more In this paper we present the findings of three longitudinal case studies in which a new method for conducting mul-timodal analysis of human behavior is tested. The focus of this new method is to engage a researcher integrally in the analysis process and allow them to guide the identifi-cation and discovery of relevant behavior instances within multimodal data. The case studies resulted in the creation of two analysis strategies: Single-Focus Hypothesis Testing and Multi-Focus Hypothesis Testing. Each were shown to be beneficial to multimodal analysis through supporting either a single focused deep analysis or analysis across multiple angles in unison. These strategies exemplified how chal-lenging questions can be answered for multimodal datasets. The new method is described and the case studies ’ find-ings are presented detailing how the new method supports multimodal analysis and opens the door for a new breed of analysis methods. Two of the three case studies resulted in publishab...
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This work investigates using n-gram processing and a temporal relation encoding to providing rela... more This work investigates using n-gram processing and a temporal relation encoding to providing relational information about events extracted from media streams. The event information is temporal and nominal in nature being categorized by a descriptive label or symbolic means and can be difficult to relationally compare and give ranking metrics. Given a parsed sequence of events, relational information pertinent to comparison between events can be obtained through the application of n-grams techniques borrowed from speech processing and temporal relation logic. The procedure is discussed along with results computed using a representative data set characterized by nominal event data. Categories and Subject Descriptors
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In desktop grids the use of off-the-shelf shared components makes the use of dedicated resources ... more In desktop grids the use of off-the-shelf shared components makes the use of dedicated resources economically nonviable and increases the complexity of design of efficient storage systems that are required to address the exponentially growing storage demands of modern applications that run on these platforms. To address this challenge, we present PeerStripe, a storage system that transparently distributes files to storage space contributed by participants that have joined a peer-to-peer (p2p) network. PeerStripe uses structured p2p routing to yield a scalable, robust, reliable, and self-organizing storage system. The novelty of PeerStripe lies in its ingenious use of striping and error coding techniques in a heterogeneous distributed environment to store very large data files. Our evaluation of PeerStripe shows that it can achieve acceptable performance for applications in desktop grids.
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Foods, 2021
This paper is concerned with extracting relevant terms from a text corpus on whisk(e)y. “Relevant... more This paper is concerned with extracting relevant terms from a text corpus on whisk(e)y. “Relevant” terms are usually contextually defined in their domain of use. Arguably, every domain has a specialized vocabulary used for describing things. For example, the field of Sensory Science, a sub-field of Food Science, investigates human responses to food products and differentiates “descriptive” terms for flavors from “ordinary”, non-descriptive language. Within the field, descriptors are generated through Descriptive Analysis, a method wherein a human panel of experts tastes multiple food products and defines descriptors. This process is both time-consuming and expensive. However, one could leverage existing data to identify and build a flavor language automatically. For example, there are thousands of professional and semi-professional reviews of whisk(e)y published on the internet, providing abundant descriptors interspersed with non-descriptive language. The aim, then, is to be able t...
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In this paper we present the findings of three longitudinal case studies in which a new method fo... more In this paper we present the findings of three longitudinal case studies in which a new method for conducting mul-timodal analysis of human behavior is tested. The focus of this new method is to engage a researcher integrally in the analysis process and allow them to guide the identifi-cation and discovery of relevant behavior instances within multimodal data. The case studies resulted in the creation of two analysis strategies: Single-Focus Hypothesis Testing and Multi-Focus Hypothesis Testing. Each were shown to be beneficial to multimodal analysis through supporting either a single focused deep analysis or analysis across multiple angles in unison. These strategies exemplified how chal-lenging questions can be answered for multimodal datasets. The new method is described and the case studies ’ find-ings are presented detailing how the new method supports multimodal analysis and opens the door for a new breed of analysis methods. Two of the three case studies resulted in publishab...
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This work investigates using n-gram processing and a temporal relation encoding to providing rela... more This work investigates using n-gram processing and a temporal relation encoding to providing relational information about events extracted from media streams. The event information is temporal and nominal in nature being categorized by a descriptive label or symbolic means and can be difficult to relationally compare and give ranking metrics. Given a parsed sequence of events, relational information pertinent to comparison between events can be obtained through the application of n-grams techniques borrowed from speech processing and temporal relation logic. The procedure is discussed along with results computed using a representative data set characterized by nominal event data. Categories and Subject Descriptors
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In desktop grids the use of off-the-shelf shared components makes the use of dedicated resources ... more In desktop grids the use of off-the-shelf shared components makes the use of dedicated resources economically nonviable and increases the complexity of design of efficient storage systems that are required to address the exponentially growing storage demands of modern applications that run on these platforms. To address this challenge, we present PeerStripe, a storage system that transparently distributes files to storage space contributed by participants that have joined a peer-to-peer (p2p) network. PeerStripe uses structured p2p routing to yield a scalable, robust, reliable, and self-organizing storage system. The novelty of PeerStripe lies in its ingenious use of striping and error coding techniques in a heterogeneous distributed environment to store very large data files. Our evaluation of PeerStripe shows that it can achieve acceptable performance for applications in desktop grids.
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Foods, 2021
This paper is concerned with extracting relevant terms from a text corpus on whisk(e)y. “Relevant... more This paper is concerned with extracting relevant terms from a text corpus on whisk(e)y. “Relevant” terms are usually contextually defined in their domain of use. Arguably, every domain has a specialized vocabulary used for describing things. For example, the field of Sensory Science, a sub-field of Food Science, investigates human responses to food products and differentiates “descriptive” terms for flavors from “ordinary”, non-descriptive language. Within the field, descriptors are generated through Descriptive Analysis, a method wherein a human panel of experts tastes multiple food products and defines descriptors. This process is both time-consuming and expensive. However, one could leverage existing data to identify and build a flavor language automatically. For example, there are thousands of professional and semi-professional reviews of whisk(e)y published on the internet, providing abundant descriptors interspersed with non-descriptive language. The aim, then, is to be able t...
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This dissertation presents a unique approach to human behavior analysis based on expert guidance ... more This dissertation presents a unique approach to human behavior analysis based on expert guidance and intervention through interactive construction and modification of behavior models. Our focus is to introduce the research area of behavior analysis, the challenges faced by this field, current approaches available, and present a new analysis approach: Interactive Relevance Search and Modeling (IRSM). More intelligent ways of conducting data analysis have been explored in recent years. Machine learning and data mining systems that utilize pattern classification and discovery in non-textual data promise to bring new generations of powerful “crawlers” for knowledge discovery, e.g., face detection and crowd surveillance. Many aspects of data can be captured by such systems, e.g., temporal information, extractable visual information—color, contrast, shape, etc. However, these captured aspects may not uncover all salient information in the data or provide adequate models/patterns of phenom...
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This dissertation presents a unique approach to human behavior analysis based on expert guidance ... more This dissertation presents a unique approach to human behavior analysis based on expert guidance and intervention through interactive construction and modification of behavior models. Our focus is to introduce the research area of behavior analysis, the challenges faced by this field, current approaches available, and present a new analysis approach: Interactive Relevance Search and Modeling (IRSM). More intelligent ways of conducting data analysis have been explored in recent years. Machine learning and data mining systems that utilize pattern classification and discovery in non-textual data promise to bring new generations of powerful “crawlers” for knowledge discovery, e.g., face detection and crowd surveillance. Many aspects of data can be captured by such systems, e.g., temporal information, extractable visual information—color, contrast, shape, etc. However, these captured aspects may not uncover all salient information in the data or provide adequate models/patterns of phenom...
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There is growing interested in discovering how to incorporate human expertise in the analysis pro... more There is growing interested in discovering how to incorporate human expertise in the analysis process. One specific question centers on how to support an expert analyzing multimodal data of human behavior over time in a way that facilitates locating subjectively relevant behavior patterns. The process of supporting such an expert begins with a seed idea that evolves over time as one investigates and searches the data. We call this kind of analysis Interactive Relevance Search and Modeling (IRSM) [4]. Many search and discovery algorithms apply statistical analysis and machine learning to identify trends in datasets. While the effectiveness of such approaches has been shown, they can alienate the user from how trends and pattern structure are discovered. They may also hide pattern details necessary to learn and identify additional trends. A transparent understanding of the underlying patterns may aid the user in the identification and discovery of behavioral trends. This can also be u...
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Groups come in various sizes and can range from a social setting with multiple smaller groups to ... more Groups come in various sizes and can range from a social setting with multiple smaller groups to a business meeting. Each group type has multiple kinds of interaction dynamics, such as bursts of activity where participants quickly exchange interaction events, e.g., quick back-and-forth speech events. This paper investigates representation and identification of interaction dynamics between participants in small group meetings using Parallel Episodes of speech events. We use meetings from the AMI corpus and identify characteristics that describe interaction dynamics. These can expedite the initial steps of analysis and provide an informed view of the interaction dynamics of a meeting.
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2019 15th International Conference on eScience (eScience), 2019
In this paper we explore the use of temporal patterns to define interaction dynamics between diff... more In this paper we explore the use of temporal patterns to define interaction dynamics between different kinds of meetings. Meetings occur on a daily basis and include different behavioral dynamics between participants, such as floor shifts and intense dialog. These dynamics can tell a story of the meeting and provide insight into how participants interact. We focus our investigation on defining diversity metrics to compare the interaction dynamics of scenario and non-scenario meetings. These metrics may be able to provide insight into the similarities and differences between scenario and non-scenario meetings. We observe that certain interaction dynamics can be identified through temporal patterns of speech intervals, i.e., when a participant is talking. We apply the principles of Parallel Episodes in identifying moments of speech overlap, e.g., interaction "bursts", and introduce Situated Data Mining, an approach for identifying repeated behavior patterns based on situated...
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Proceedings of the 20th ACM international conference on Multimedia - MM '12, 2012
ABSTRACT The presented thesis work addresses how social scientists may derive patterns of human b... more ABSTRACT The presented thesis work addresses how social scientists may derive patterns of human behavior captured in media streams. Currently, media streams are being segmented into sequences of events describing the actions captured in the streams, such as the interactions among humans. This segmentation creates a challenging data space to search characterized by non-numerical, temporal, descriptive data, e.g., Person A walks up to Person B at time T. We present an approach that allows one to interactively search and discover temporal behavior patterns within such a data space.
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Proceedings of the 15th ACM on International conference on multimodal interaction - ICMI '13, 2013
ABSTRACT In this paper we present the findings of three longitudinal case studies in which a new ... more ABSTRACT In this paper we present the findings of three longitudinal case studies in which a new method for conducting multimodal analysis of human behavior is tested. The focus of this new method is to engage a researcher integrally in the analysis process and allow them to guide the identification and discovery of relevant behavior instances within multimodal data. The case studies resulted in the creation of two analysis strategies: Single-Focus Hypothesis Testing and Multi-Focus Hypothesis Testing. Each were shown to be beneficial to multimodal analysis through supporting either a single focused deep analysis or analysis across multiple angles in unison. These strategies exemplified how challenging questions can be answered for multimodal datasets. The new method is described and the case studies' findings are presented detailing how the new method supports multimodal analysis and opens the door for a new breed of analysis methods. Two of the three case studies resulted in publishable results for the respective participants.
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Proceedings of the 14th ACM international conference on Multimodal interaction - ICMI '12, 2012
Abstract There are a multitude of annotated behavior corpora (manual and automatic annotations) a... more Abstract There are a multitude of annotated behavior corpora (manual and automatic annotations) available as research expands in multimodal analysis of human behavior. Despite the rich representations within these datasets, search strategies are limited with respect to the advanced representations and complex structures describing human interaction sequences. The relationships amongst human interactions are structural in nature. Hence, we present Structural and Temporal Inference Search (STIS) to support ...
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Journal of eScience Librarianship
Objective: An area of research in which open science may have particularly high impact is in deep... more Objective: An area of research in which open science may have particularly high impact is in deep learning (DL), where researchers have developed many algorithms to solve challenging problems, but others may have difficulty in replicating results and applying these algorithms. In response, some researchers have begun to open up DL research by making their resources available (e.g., code, datasets and/or pre-trained models) to the research community. This article describes three case studies in DL where openly available resources are used and we investigate the impact on the projects, the outcomes, and make recommendations for what to focus on when making DL resources available.Methods: Each case study represents a single project using openly available DL resources for a research project. The process and progress of each case study is recorded along with aspects such as approaches taken, documentation of openly available resources, and researchers' experience with the openly avai...
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In this paper we present the findings of three longitudinal case studies in which a new method fo... more In this paper we present the findings of three longitudinal case studies in which a new method for conducting mul-timodal analysis of human behavior is tested. The focus of this new method is to engage a researcher integrally in the analysis process and allow them to guide the identifi-cation and discovery of relevant behavior instances within multimodal data. The case studies resulted in the creation of two analysis strategies: Single-Focus Hypothesis Testing and Multi-Focus Hypothesis Testing. Each were shown to be beneficial to multimodal analysis through supporting either a single focused deep analysis or analysis across multiple angles in unison. These strategies exemplified how chal-lenging questions can be answered for multimodal datasets. The new method is described and the case studies ’ find-ings are presented detailing how the new method supports multimodal analysis and opens the door for a new breed of analysis methods. Two of the three case studies resulted in publishab...
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This work investigates using n-gram processing and a temporal relation encoding to providing rela... more This work investigates using n-gram processing and a temporal relation encoding to providing relational information about events extracted from media streams. The event information is temporal and nominal in nature being categorized by a descriptive label or symbolic means and can be difficult to relationally compare and give ranking metrics. Given a parsed sequence of events, relational information pertinent to comparison between events can be obtained through the application of n-grams techniques borrowed from speech processing and temporal relation logic. The procedure is discussed along with results computed using a representative data set characterized by nominal event data. Categories and Subject Descriptors
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In desktop grids the use of off-the-shelf shared components makes the use of dedicated resources ... more In desktop grids the use of off-the-shelf shared components makes the use of dedicated resources economically nonviable and increases the complexity of design of efficient storage systems that are required to address the exponentially growing storage demands of modern applications that run on these platforms. To address this challenge, we present PeerStripe, a storage system that transparently distributes files to storage space contributed by participants that have joined a peer-to-peer (p2p) network. PeerStripe uses structured p2p routing to yield a scalable, robust, reliable, and self-organizing storage system. The novelty of PeerStripe lies in its ingenious use of striping and error coding techniques in a heterogeneous distributed environment to store very large data files. Our evaluation of PeerStripe shows that it can achieve acceptable performance for applications in desktop grids.
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Foods, 2021
This paper is concerned with extracting relevant terms from a text corpus on whisk(e)y. “Relevant... more This paper is concerned with extracting relevant terms from a text corpus on whisk(e)y. “Relevant” terms are usually contextually defined in their domain of use. Arguably, every domain has a specialized vocabulary used for describing things. For example, the field of Sensory Science, a sub-field of Food Science, investigates human responses to food products and differentiates “descriptive” terms for flavors from “ordinary”, non-descriptive language. Within the field, descriptors are generated through Descriptive Analysis, a method wherein a human panel of experts tastes multiple food products and defines descriptors. This process is both time-consuming and expensive. However, one could leverage existing data to identify and build a flavor language automatically. For example, there are thousands of professional and semi-professional reviews of whisk(e)y published on the internet, providing abundant descriptors interspersed with non-descriptive language. The aim, then, is to be able t...
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In this paper we present the findings of three longitudinal case studies in which a new method fo... more In this paper we present the findings of three longitudinal case studies in which a new method for conducting mul-timodal analysis of human behavior is tested. The focus of this new method is to engage a researcher integrally in the analysis process and allow them to guide the identifi-cation and discovery of relevant behavior instances within multimodal data. The case studies resulted in the creation of two analysis strategies: Single-Focus Hypothesis Testing and Multi-Focus Hypothesis Testing. Each were shown to be beneficial to multimodal analysis through supporting either a single focused deep analysis or analysis across multiple angles in unison. These strategies exemplified how chal-lenging questions can be answered for multimodal datasets. The new method is described and the case studies ’ find-ings are presented detailing how the new method supports multimodal analysis and opens the door for a new breed of analysis methods. Two of the three case studies resulted in publishab...
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This work investigates using n-gram processing and a temporal relation encoding to providing rela... more This work investigates using n-gram processing and a temporal relation encoding to providing relational information about events extracted from media streams. The event information is temporal and nominal in nature being categorized by a descriptive label or symbolic means and can be difficult to relationally compare and give ranking metrics. Given a parsed sequence of events, relational information pertinent to comparison between events can be obtained through the application of n-grams techniques borrowed from speech processing and temporal relation logic. The procedure is discussed along with results computed using a representative data set characterized by nominal event data. Categories and Subject Descriptors
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In desktop grids the use of off-the-shelf shared components makes the use of dedicated resources ... more In desktop grids the use of off-the-shelf shared components makes the use of dedicated resources economically nonviable and increases the complexity of design of efficient storage systems that are required to address the exponentially growing storage demands of modern applications that run on these platforms. To address this challenge, we present PeerStripe, a storage system that transparently distributes files to storage space contributed by participants that have joined a peer-to-peer (p2p) network. PeerStripe uses structured p2p routing to yield a scalable, robust, reliable, and self-organizing storage system. The novelty of PeerStripe lies in its ingenious use of striping and error coding techniques in a heterogeneous distributed environment to store very large data files. Our evaluation of PeerStripe shows that it can achieve acceptable performance for applications in desktop grids.
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
Foods, 2021
This paper is concerned with extracting relevant terms from a text corpus on whisk(e)y. “Relevant... more This paper is concerned with extracting relevant terms from a text corpus on whisk(e)y. “Relevant” terms are usually contextually defined in their domain of use. Arguably, every domain has a specialized vocabulary used for describing things. For example, the field of Sensory Science, a sub-field of Food Science, investigates human responses to food products and differentiates “descriptive” terms for flavors from “ordinary”, non-descriptive language. Within the field, descriptors are generated through Descriptive Analysis, a method wherein a human panel of experts tastes multiple food products and defines descriptors. This process is both time-consuming and expensive. However, one could leverage existing data to identify and build a flavor language automatically. For example, there are thousands of professional and semi-professional reviews of whisk(e)y published on the internet, providing abundant descriptors interspersed with non-descriptive language. The aim, then, is to be able t...
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This dissertation presents a unique approach to human behavior analysis based on expert guidance ... more This dissertation presents a unique approach to human behavior analysis based on expert guidance and intervention through interactive construction and modification of behavior models. Our focus is to introduce the research area of behavior analysis, the challenges faced by this field, current approaches available, and present a new analysis approach: Interactive Relevance Search and Modeling (IRSM). More intelligent ways of conducting data analysis have been explored in recent years. Machine learning and data mining systems that utilize pattern classification and discovery in non-textual data promise to bring new generations of powerful “crawlers” for knowledge discovery, e.g., face detection and crowd surveillance. Many aspects of data can be captured by such systems, e.g., temporal information, extractable visual information—color, contrast, shape, etc. However, these captured aspects may not uncover all salient information in the data or provide adequate models/patterns of phenom...
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This dissertation presents a unique approach to human behavior analysis based on expert guidance ... more This dissertation presents a unique approach to human behavior analysis based on expert guidance and intervention through interactive construction and modification of behavior models. Our focus is to introduce the research area of behavior analysis, the challenges faced by this field, current approaches available, and present a new analysis approach: Interactive Relevance Search and Modeling (IRSM). More intelligent ways of conducting data analysis have been explored in recent years. Machine learning and data mining systems that utilize pattern classification and discovery in non-textual data promise to bring new generations of powerful “crawlers” for knowledge discovery, e.g., face detection and crowd surveillance. Many aspects of data can be captured by such systems, e.g., temporal information, extractable visual information—color, contrast, shape, etc. However, these captured aspects may not uncover all salient information in the data or provide adequate models/patterns of phenom...
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There is growing interested in discovering how to incorporate human expertise in the analysis pro... more There is growing interested in discovering how to incorporate human expertise in the analysis process. One specific question centers on how to support an expert analyzing multimodal data of human behavior over time in a way that facilitates locating subjectively relevant behavior patterns. The process of supporting such an expert begins with a seed idea that evolves over time as one investigates and searches the data. We call this kind of analysis Interactive Relevance Search and Modeling (IRSM) [4]. Many search and discovery algorithms apply statistical analysis and machine learning to identify trends in datasets. While the effectiveness of such approaches has been shown, they can alienate the user from how trends and pattern structure are discovered. They may also hide pattern details necessary to learn and identify additional trends. A transparent understanding of the underlying patterns may aid the user in the identification and discovery of behavioral trends. This can also be u...
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Groups come in various sizes and can range from a social setting with multiple smaller groups to ... more Groups come in various sizes and can range from a social setting with multiple smaller groups to a business meeting. Each group type has multiple kinds of interaction dynamics, such as bursts of activity where participants quickly exchange interaction events, e.g., quick back-and-forth speech events. This paper investigates representation and identification of interaction dynamics between participants in small group meetings using Parallel Episodes of speech events. We use meetings from the AMI corpus and identify characteristics that describe interaction dynamics. These can expedite the initial steps of analysis and provide an informed view of the interaction dynamics of a meeting.
Bookmarks Related papers MentionsView impact
2019 15th International Conference on eScience (eScience), 2019
In this paper we explore the use of temporal patterns to define interaction dynamics between diff... more In this paper we explore the use of temporal patterns to define interaction dynamics between different kinds of meetings. Meetings occur on a daily basis and include different behavioral dynamics between participants, such as floor shifts and intense dialog. These dynamics can tell a story of the meeting and provide insight into how participants interact. We focus our investigation on defining diversity metrics to compare the interaction dynamics of scenario and non-scenario meetings. These metrics may be able to provide insight into the similarities and differences between scenario and non-scenario meetings. We observe that certain interaction dynamics can be identified through temporal patterns of speech intervals, i.e., when a participant is talking. We apply the principles of Parallel Episodes in identifying moments of speech overlap, e.g., interaction "bursts", and introduce Situated Data Mining, an approach for identifying repeated behavior patterns based on situated...
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Bookmarks Related papers MentionsView impact
Proceedings of the 20th ACM international conference on Multimedia - MM '12, 2012
ABSTRACT The presented thesis work addresses how social scientists may derive patterns of human b... more ABSTRACT The presented thesis work addresses how social scientists may derive patterns of human behavior captured in media streams. Currently, media streams are being segmented into sequences of events describing the actions captured in the streams, such as the interactions among humans. This segmentation creates a challenging data space to search characterized by non-numerical, temporal, descriptive data, e.g., Person A walks up to Person B at time T. We present an approach that allows one to interactively search and discover temporal behavior patterns within such a data space.
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Proceedings of the 15th ACM on International conference on multimodal interaction - ICMI '13, 2013
ABSTRACT In this paper we present the findings of three longitudinal case studies in which a new ... more ABSTRACT In this paper we present the findings of three longitudinal case studies in which a new method for conducting multimodal analysis of human behavior is tested. The focus of this new method is to engage a researcher integrally in the analysis process and allow them to guide the identification and discovery of relevant behavior instances within multimodal data. The case studies resulted in the creation of two analysis strategies: Single-Focus Hypothesis Testing and Multi-Focus Hypothesis Testing. Each were shown to be beneficial to multimodal analysis through supporting either a single focused deep analysis or analysis across multiple angles in unison. These strategies exemplified how challenging questions can be answered for multimodal datasets. The new method is described and the case studies' findings are presented detailing how the new method supports multimodal analysis and opens the door for a new breed of analysis methods. Two of the three case studies resulted in publishable results for the respective participants.
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Proceedings of the 14th ACM international conference on Multimodal interaction - ICMI '12, 2012
Abstract There are a multitude of annotated behavior corpora (manual and automatic annotations) a... more Abstract There are a multitude of annotated behavior corpora (manual and automatic annotations) available as research expands in multimodal analysis of human behavior. Despite the rich representations within these datasets, search strategies are limited with respect to the advanced representations and complex structures describing human interaction sequences. The relationships amongst human interactions are structural in nature. Hence, we present Structural and Temporal Inference Search (STIS) to support ...
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