System and method for mining of temporal data
View Patent ↗A system for temporal data mining includes a computer readable medium having an application configured to receive at an input module a temporal data series having events with start times and end times, a set of allowed dwelling times and a threshold frequency. The system is further configured to identify, using a candidate identification and tracking module, one or more occurrences in the temporal data series of a candidate episode and increment a count for each identified occurrence. The system is also configured to produce at an output module an output for those episodes whose count of occurrences results in a frequency exceeding the threshold frequency.
1. A computer-readable storage medium tangibly embodying executable instructions for:
receiving as input a temporal data series comprising events with start times and end times, a set of allowed dwelling times, a threshold frequency of occurrence, and an expiry time, wherein the expiry time provides a criterion for occurrence of an episode;
finding all frequent principal episodes of a particular length in the temporal data series having dwelling times, as determined by the start and end times, within the allowed dwelling times;
in successive passes through the temporal data series:
incrementing the particular length to generate an increased length;
combining frequent principal episodes to create combined episodes of the increased length;
creating a set of candidate episodes from the combined episodes by removing combined episodes which have non-frequent sub-episodes;
identifying one or more occurrences of a candidate episode in the temporal data series, wherein the identifying comprises tracking, with a plurality of automata, whether an occurrence of a candidate episode occurs in the temporal data series;
generating the plurality of automata configured to track whether an occurrence of a candidate episode occurs in the temporal data series, wherein the plurality of automata are configured to track a non-overlapping occurrence of a candidate episode;
incrementing a count for each identified occurrence;
determining frequent principal episodes of the increased length;
setting the particular length to the increased length; and
producing an output for frequent principal episodes, wherein a frequent principal episode is a principal episode whose count of occurrences results in a frequency meeting or exceeding the threshold frequency of occurrence.
2. The computer-readable storage medium of claim 1 , wherein the identifying comprises identifying whether a non-interleaved occurrence of a candidate episode occurs in the temporal data series.
3. The computer-readable storage medium of claim 1 , wherein the plurality of automata are configured to track a non-interleaved occurrence of a candidate episode.
4. A system for temporal data mining, comprising:
a computer readable storage medium that includes an application configured to:
receive at an input module a temporal data series comprising events with start times and end times, a set of allowed dwelling times, and a threshold frequency of occurrence, wherein the input module receives an expiry time for providing a criterion for occurrence of an episode;
identify using a candidate identification and tracking module one or more occurrences in the temporal data series of a candidate episode having dwelling times, as determined by the start and end times, within the allowed dwelling times,
in successive passes through the temporal data series:
increment the particular length to generate an increased length;
combine frequent principal episodes to create combined episodes of the increased length;
create a set of candidate episodes from the combined episodes by removing combined episodes which have non-frequent sub-episodes;
identifying one or more occurrences of a candidate episode in the temporal data series, wherein the identifying comprises tracking, with a plurality of automata, whether an occurrence of a candidate episode occurs in the temporal data series;
generate using an automata generation module the plurality of automata configured to track whether an occurrence of a candidate episode occurs in the temporal data series, wherein the plurality of automata are configured to track a non-overlapping occurrence of a candidate episode and;
increment a count for each identified occurrence;
determine frequent principal episodes of the increased length;
set the particular length to the increased length; and
produce at an output module an output for those episodes which are principal and whose count of occurrences results in a frequency meeting or exceeding the threshold frequency of occurrence.
5. The system of claim 4 , wherein the candidate identification and tracking module identifies whether a non-interleaved occurrence of a candidate episode occurs in the temporal data series.
6. The system of claim 4 , wherein the plurality of automata are adapted configured to track a non-interleaved occurrence of a candidate episode.
7. An apparatus for temporal data mining, comprising:
a processor for executing instructions;
a memory device including instructions comprising:
input instructions for receiving a temporal data series comprising events with start times and end times, a set of allowed dwelling times, a threshold frequency of occurrence, and an expiry time, wherein the expiry time provides a criterion for occurrence of an episode;
candidate identification and tracking instructions for identifying one or more occurrences in the temporal data series of a candidate episode having dwelling times, as determined by the start and end times, within the allowed dwelling times,
in successive passes through the temporal data series:
increment the particular length to generate an increased length;
combine frequent principal episodes to create combined episodes of the increased length;
create a set of candidate episodes from the combined episodes by removing combined episodes which have non-frequent sub-episodes;
identify one or more occurrences of a candidate episode in the temporal data series, wherein the identifying comprises tracking, with a plurality of automata, whether an occurrence of a candidate episode occurs in the temporal data series;
instructions for generating a plurality of automata configured to track whether an occurrence of a candidate episode occurs in the temporal data series, wherein the plurality of automata are configured to track a non-overlapping occurrence of a candidate episode;
increment a count for each identified occurrence;
determine frequent principal episodes of the increased length;
set the particular length to the increased length; and
output instructions for producing an output for those episodes which are principal and whose count of occurrences results in a frequency meeting or exceeding the threshold frequency of occurrence.
8. The apparatus of claim 7 , wherein the candidate identification and tracking instructions comprise instructions for identifying whether a non-interleaved occurrence of a candidate episode occurs in the temporal data series.
9. The apparatus of claim 7 , wherein the plurality of automata are adapted to track a non-interleaved occurrence of a candidate episode.