DETECTIVE METHOD AND SYSTEM FOR ACTIVITY-OR-BEHAVIOR MODEL CONSTRUCTION AND AUTOMATIC DETECTION OF THE ABNORMAL ACTIVITIES OR BEHAVIORS OF A SUBJECT SYSTEM WITHOUT REQUIRING PRIOR DOMAIN KNOWLEDGE
According to one embodiment of the invention, a detective method, applied in a detective system comprising a activity-or-behavior model constructor, for activity-or-behavior model construction and automatic detection of activities of a subject system, comprising steps of: using an unsupervised machi...
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Format | Patent |
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Language | English |
Published |
28.12.2017
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Online Access | Get full text |
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Abstract | According to one embodiment of the invention, a detective method, applied in a detective system comprising a activity-or-behavior model constructor, for activity-or-behavior model construction and automatic detection of activities of a subject system, comprising steps of: using an unsupervised machine learning technique to preprocess and analyze raw sensor data obtained from the monitored subject system to generate post data; with the post data as input, using a Natural Language Processing technique (NLP) to discover the activities or behaviors performed by the subject system; and with output data from the NLP technique as input, using a surprised machine learning technique to build an activity-or-behavior model for predicting the future behaviors of the subject system and automatically detecting abnormal activities or behaviors of the subject system; wherein the activity-or-behavior model is capable to handle multidimensional sensor data input from a plurality of sensor data streams and incorporate the sensor data values and a selected temporal information about at least one sensor data stream and between different sensor data streams. |
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AbstractList | According to one embodiment of the invention, a detective method, applied in a detective system comprising a activity-or-behavior model constructor, for activity-or-behavior model construction and automatic detection of activities of a subject system, comprising steps of: using an unsupervised machine learning technique to preprocess and analyze raw sensor data obtained from the monitored subject system to generate post data; with the post data as input, using a Natural Language Processing technique (NLP) to discover the activities or behaviors performed by the subject system; and with output data from the NLP technique as input, using a surprised machine learning technique to build an activity-or-behavior model for predicting the future behaviors of the subject system and automatically detecting abnormal activities or behaviors of the subject system; wherein the activity-or-behavior model is capable to handle multidimensional sensor data input from a plurality of sensor data streams and incorporate the sensor data values and a selected temporal information about at least one sensor data stream and between different sensor data streams. |
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Snippet | According to one embodiment of the invention, a detective method, applied in a detective system comprising a activity-or-behavior model constructor, for... |
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Title | DETECTIVE METHOD AND SYSTEM FOR ACTIVITY-OR-BEHAVIOR MODEL CONSTRUCTION AND AUTOMATIC DETECTION OF THE ABNORMAL ACTIVITIES OR BEHAVIORS OF A SUBJECT SYSTEM WITHOUT REQUIRING PRIOR DOMAIN KNOWLEDGE |
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