Patents by Inventor Yanjia Sun
Yanjia Sun has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 10489363Abstract: The disclosure relates to technology for mining data in a database by recursively mining a conditional frequent pattern tree (FP-tree) for frequent items of each conditional pattern base for each node in an FP-tree to obtain frequent patterns. For each branch in the FP-tree, a single-item node table (NT) is generated for which a selected one of the frequent items appears in the node of the branch. The single-item NT including a list of all of the frequent items appearing in the FP-tree and a corresponding frequent item count. For each single-item NT of each branch generated for the selected one of the frequent items, the frequent item count of each frequent item is summed in the single-item NT formed for each branch to generate a combined single-item NT, and association rules based on the frequent patterns are generated for each of the frequent items and the combined single-item NT.Type: GrantFiled: October 19, 2016Date of Patent: November 26, 2019Assignee: Futurewei Technologies, Inc.Inventors: Kai Yang, Tao Quan, Yanjia Sun
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Patent number: 10482158Abstract: Techniques are provided for monitoring the performance of a user device in a communication network. The techniques include detecting an anomaly in a performance measurement such as a key quality indicator (KQI) of the user device. The techniques include obtaining historical measurements of the KQI for user devices. The historical measurements are assigned to states to reflect whether the performance is good or bad, or somewhere in between. The states can be defined differently for different hours in the day so that the states represent the relative performance for that time of day. For each user device, a Markov model is provided indicating probabilities of transitions between the states. Additional measurements are obtained of the KQI for a selected user device, and the Markov model of the selected user device is used to detect an anomaly in the additional measurements.Type: GrantFiled: March 31, 2017Date of Patent: November 19, 2019Assignee: Futurewei Technologies, Inc.Inventors: Kai Yang, Yanjia Sun, Ruilin Liu, Deti Liu, Jin Yang
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Patent number: 10397810Abstract: A processor implemented method of identifying a root cause of degraded network quality in a wireless network. The method includes accessing historical network performance data, the performance data including a time sequenced measure of performance indicators for the network. The method evaluates the historical performance data to determine regularly occurring associations between indicators to define a set of rules characterizing the associations of the wireless network, and stores the set of rules in a data structure. The wireless network is monitored by accessing analysis data reporting time sequenced performance indicator data. Next, anomalies are detected in a performance indicator in the analysis data and matched to at least one rule in the set of rules. The method outputs an indication of a cause of degradation in the wireless network resulting from the anomaly in the performance indicator.Type: GrantFiled: January 8, 2016Date of Patent: August 27, 2019Assignee: Futurewei Technologies, Inc.Inventors: Kai Yang, Yanjia Sun, Ruilin Liu, Jin Yang
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Patent number: 10332056Abstract: The disclosure relates to technology for processing data sets to generate data rules for the data sets in a communications network. A first set of data including key quality indicators (KQIs) indicative of a quality of service and a second set of data including key performance indicators (KPIs) indicative of a performance level are received. The first data set and the second data set are categorized using a first value into a plurality of KQI groups and a second value into a plurality of KPI groups, respectively. Each of the KQI and KPI groups are identified with a label. Each of the KQI and KPI groups identified with a same label are processed by application of association rule learning to generate the data rules. The data rules model a relationship between the KQIs and the KPIs by calculating association frequencies.Type: GrantFiled: March 14, 2016Date of Patent: June 25, 2019Assignee: Futurewei Technologies, Inc.Inventors: Kai Yang, Yanjia Sun, Ruilin Liu
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Publication number: 20180285320Abstract: Techniques are provided for monitoring the performance of a user device in a communication network. The techniques include detecting an anomaly in a performance measurement such as a key quality indicator (KQI) of the user device. The techniques include obtaining historical measurements of the KQI for user devices. The historical measurements are assigned to states to reflect whether the performance is good or bad, or somewhere in between. The states can be defined differently for different hours in the day so that the states represent the relative performance for that time of day. For each user device, a Markov model is provided indicating probabilities of transitions between the states. Additional measurements are obtained of the KQI for a selected user device, and the Markov model of the selected user device is used to detect an anomaly in the additional measurements.Type: ApplicationFiled: March 31, 2017Publication date: October 4, 2018Applicant: Futurewei Technologies, Inc.Inventors: Kai Yang, Yanjia Sun, Ruilin Liu, Deti Liu, Jin Yang
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Patent number: 9961571Abstract: A system and method for detecting anomalies in a communication network includes detecting first outliers in a first set of quality indicators for a cellular group, detecting second outliers in a second set of performance indicators for the cellular group, correlating the first outliers and the second outliers to produce an anomaly candidate, determining a confidence threshold for the anomaly candidate, and indicating a network anomaly in response to the confidence threshold exceeding a predetermined threshold.Type: GrantFiled: September 24, 2015Date of Patent: May 1, 2018Assignee: Futurewei Technologies, Inc.Inventors: Kai Yang, Ruilin Liu, Yanjia Sun
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Publication number: 20180107695Abstract: The disclosure relates to technology for mining data in a database by recursively mining a conditional frequent pattern tree (FP-tree) for frequent items of each conditional pattern base for each node in an FP-tree to obtain frequent patterns. For each branch in the FP-tree, a single-item node table (NT) is generated for which a selected one of the frequent items appears in the node of the branch. The single-item NT including a list of all of the frequent items appearing in the FP-tree and a corresponding frequent item count. For each single-item NT of each branch generated for the selected one of the frequent items, the frequent item count of each frequent item is summed in the single-item NT formed for each branch to generate a combined single-item NT, and association rules based on the frequent patterns are generated for each of the frequent items and the combined single-item NT.Type: ApplicationFiled: October 19, 2016Publication date: April 19, 2018Applicant: Futurewei Technologies, Inc.Inventors: Kai Yang, Tao Quan, Yanjia Sun
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Publication number: 20170262781Abstract: The disclosure relates to technology for processing data sets to generate data rules for the data sets in a communications network. A first set of data including key quality indicators (KQIs) indicative of a quality of service and a second set of data including key performance indicators (KPIs) indicative of a performance level are received. The first data set and the second data set are categorized using a first value into a plurality of KQI groups and a second value into a plurality of KPI groups, respectively. Each of the KQI and KPI groups are identified with a label. Each of the KQI and KPI groups identified with a same label are processed by application of association rule learning to generate the data rules. The data rules model a relationship between the KQIs and the KPIs by calculating association frequencies.Type: ApplicationFiled: March 14, 2016Publication date: September 14, 2017Applicant: Futurewei Technologies, Inc.Inventors: Kai Yang, Yanjia Sun, Ruilin Liu
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Publication number: 20170201897Abstract: A processor implemented method of identifying a root cause of degraded network quality in a wireless network. The method includes accessing historical network performance data, the performance data including a time sequenced measure of performance indicators for the network. The method evaluates the historical performance data to determine regularly occurring associations between indicators to define a set of rules characterizing the associations of the wireless network, and stores the set of rules in a data structure. The wireless network is monitored by accessing analysis data reporting time sequenced performance indicator data. Next, anomalies are detected in a performance indicator in the analysis data and matched to at least one rule in the set of rules. The method outputs an indication of a cause of degradation in the wireless network resulting from the anomaly in the performance indicator.Type: ApplicationFiled: January 8, 2016Publication date: July 13, 2017Inventors: Kai Yang, Yanjia Sun, Ruilin Liu, Jin Yang
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Publication number: 20170094537Abstract: A system and method for detecting anomalies in a communication network includes detecting first outliers in a first set of quality indicators for a cellular group, detecting second outliers in a second set of performance indicators for the cellular group, correlating the first outliers and the second outliers to produce an anomaly candidate, determining a confidence threshold for the anomaly candidate, and indicating a network anomaly in response to the confidence threshold exceeding a predetermined threshold.Type: ApplicationFiled: September 24, 2015Publication date: March 30, 2017Inventors: Kai Yang, Ruilin Liu, Yanjia Sun