title: Improving the performance of Hierarchical Hidden Markov Models on Information Extraction tasks

authors: Chou, Lin-Yi

subjects: hidden Markov model

abstract: This thesis presents novel methods for creating and improving hierarchical hidden Markov models.  The work centers around transforming a traditional tree structured hierarchical hidden Markov model (HHMM) into an equivalent model that reuses repeated sub-trees.  This process temporarily breaks the tree structure constraint in order to leverage the benefits of combining repeated sub-trees. These benefits include lowered cost of testing and an increased accuracy of the final model-thus providing the model with greater performance.  The result is called a merged and simplified hierarchical hidden Markov model (MSHHMM).

The thesis goes on to detail four techniques for improving the performance of MSHHMMs when applied to information extraction tasks, in terms of accuracy and computational cost.  Briefly, these techniques are: a new formula for calculating the approximate probability of previously unseen events; pattern generalisation to transform observations, thus increasing testing speed and prediction accuracy; restructuring states to focus on state transitions; and an automated flattening technique for reducing the complexity of HHMMs.

The basic model and four improvements are evaluated by applying them to the well-known information extraction tasks of Reference Tagging and Text Chunking.  In both tasks, MSHHMMs show consistently good performance across varying sizes of training data. In the case of Reference Tagging, the accuracy of the MSHHMM is comparable to other methods. However, when the volume of training data is limited, MSHHMMs maintain high accuracy whereas other methods show a significant decrease.  These accuracy gains were achieved without any significant increase in processing time.  For the Text Chunking task the accuracy of the MSHHMM was again comparable to other methods. However, the other methods incurred much higher processing delays compared to the MSHHMM.  The results of these practical experiments demonstrate the benefits of the new method-increased accuracy, lower computation costs, and better performance.

text: Improving the performance of Hierarchical Hidden Markov Models on Information Extraction tasks This thesis presents novel methods for creating and improving hierarchical hidden Markov models.  The work centers around transforming a traditional tree structured hierarchical hidden Markov model (HHMM) into an equivalent model that reuses repeated sub-trees.  This process temporarily breaks the tree structure constraint in order to leverage the benefits of combining repeated sub-trees. These benefits include lowered cost of testing and an increased accuracy of the final model-thus providing the model with greater performance.  The result is called a merged and simplified hierarchical hidden Markov model (MSHHMM).

The thesis goes on to detail four techniques for improving the performance of MSHHMMs when applied to information extraction tasks, in terms of accuracy and computational cost.  Briefly, these techniques are: a new formula for calculating the approximate probability of previously unseen events; pattern generalisation to transform observations, thus increasing testing speed and prediction accuracy; restructuring states to focus on state transitions; and an automated flattening technique for reducing the complexity of HHMMs.

The basic model and four improvements are evaluated by applying them to the well-known information extraction tasks of Reference Tagging and Text Chunking.  In both tasks, MSHHMMs show consistently good performance across varying sizes of training data. In the case of Reference Tagging, the accuracy of the MSHHMM is comparable to other methods. However, when the volume of training data is limited, MSHHMMs maintain high accuracy whereas other methods show a significant decrease.  These accuracy gains were achieved without any significant increase in processing time.  For the Text Chunking task the accuracy of the MSHHMM was again comparable to other methods. However, the other methods incurred much higher processing delays compared to the MSHHMM.  The results of these practical experiments demonstrate the benefits of the new method-increased accuracy, lower computation costs, and better performance.

year: 2006

title: Reliability of overground running measures from 2D video Analyses in a field environment.

authors: Murray, Lauralee

subjects: biomechanics

abstract: Two-dimensional running analyses are common in research and practice, and have been shown to be reliable when conducted on a treadmill. However, running is typically performed outdoors. Our aim was to determine the intra- and inter-rater reliability of two-dimensional analyses of overground running in an outdoor environment. Two raters independently evaluated 155 high-speed videos (240 Hz) of overground running from recreationally competitive runners on two occasions, seven days apart (test-retest study design). The reliability of foot-strike pattern (rear-foot, mid-foot, and fore-foot), foot-strike angle (°), and running speed (m/s) was assessed using weighted kappa (κ), percentage agreement, intraclass correlation coefficient (ICC), typical error (TE), and coefficient of variation (CV) statistics. Foot-strike pattern (agreement = 99.4%, κ = 0.96) and running speed (ICC = 0.98, TE = 0.09 m/s, CV = 2.1%) demonstrated excellent relative and absolute reliability. Foot-strike angle exhibited high relative reliability (ICC = 0.88), but suboptimal absolute reliability (TE = 2.5°, CV = 17.6%). Two-dimensional analyses of overground running outdoors were reliable for quantifying foot-strike pattern, foot-strike angle, and running speed, although foot-strike angle errors of 2.5° were typical. Foot-strike angle changes of less than 2.5° should be interpreted with caution in clinical settings, as they might simply reflect measurement errors.

text: Reliability of overground running measures from 2D video Analyses in a field environment. Two-dimensional running analyses are common in research and practice, and have been shown to be reliable when conducted on a treadmill. However, running is typically performed outdoors. Our aim was to determine the intra- and inter-rater reliability of two-dimensional analyses of overground running in an outdoor environment. Two raters independently evaluated 155 high-speed videos (240 Hz) of overground running from recreationally competitive runners on two occasions, seven days apart (test-retest study design). The reliability of foot-strike pattern (rear-foot, mid-foot, and fore-foot), foot-strike angle (°), and running speed (m/s) was assessed using weighted kappa (κ), percentage agreement, intraclass correlation coefficient (ICC), typical error (TE), and coefficient of variation (CV) statistics. Foot-strike pattern (agreement = 99.4%, κ = 0.96) and running speed (ICC = 0.98, TE = 0.09 m/s, CV = 2.1%) demonstrated excellent relative and absolute reliability. Foot-strike angle exhibited high relative reliability (ICC = 0.88), but suboptimal absolute reliability (TE = 2.5°, CV = 17.6%). Two-dimensional analyses of overground running outdoors were reliable for quantifying foot-strike pattern, foot-strike angle, and running speed, although foot-strike angle errors of 2.5° were typical. Foot-strike angle changes of less than 2.5° should be interpreted with caution in clinical settings, as they might simply reflect measurement errors.

year: 2018

title: Alice Grey Nicholls, daughter of William, and her husband, Charles John Dearle

authors: Hart, Philip

abstract: Alice Grey Nicholls was the ‘half-caste’ daughter of a Pakeha Maori, William Nicholls. She would marry a Pakeha and have several children, losing her only son but bringing up a family of daughters, who all received a Pakeha education. Having a moko emphasized her Maori heritage, and she was on good terms with many Maori.
Charles John Dearle, a Londoner, after some involvement in gold mining spent most of his life working for the government. At the request of Maori landowners, from 1883 until 1895 he allocated goldfields revenue amongst them, a challenging task. He was also involved in land purchases both on behalf of the government and for personal gain. 
They farmed her land at Mangaiti, near Te Aroha, Alice continuing to farm it profitably after his early death, assisted for a time by her daughters. She purchased more land, and to enable her to sell some portions of it she had it declared European land, an illustration of her astuteness in business; her family obtained a good financial position from her farming and land dealings. When she died, aged 81, her Pakeha friends fondly remembered her.

text: Alice Grey Nicholls, daughter of William, and her husband, Charles John Dearle Alice Grey Nicholls was the ‘half-caste’ daughter of a Pakeha Maori, William Nicholls. She would marry a Pakeha and have several children, losing her only son but bringing up a family of daughters, who all received a Pakeha education. Having a moko emphasized her Maori heritage, and she was on good terms with many Maori.
Charles John Dearle, a Londoner, after some involvement in gold mining spent most of his life working for the government. At the request of Maori landowners, from 1883 until 1895 he allocated goldfields revenue amongst them, a challenging task. He was also involved in land purchases both on behalf of the government and for personal gain. 
They farmed her land at Mangaiti, near Te Aroha, Alice continuing to farm it profitably after his early death, assisted for a time by her daughters. She purchased more land, and to enable her to sell some portions of it she had it declared European land, an illustration of her astuteness in business; her family obtained a good financial position from her farming and land dealings. When she died, aged 81, her Pakeha friends fondly remembered her.

year: 2016