EXTRACTING RELATED CONCEPTS FROM A CONTENT STREAM USING TEMPORAL DISTRIBUTION

1 . A method comprising

extracting candidate phrases from a content stream;

thresholding the candidate phrases below a minimum frequency for each candidate phrase;

determining a temporal distribution of the candidate phrases;

determining interestingness of the candidate phrases,

wherein determining interestingness of the candidate phrases comprises statistically analyzing the temporal distribution of a candidate phrase; and

displaying the candidate phrases.

2 . The method of claim 1 , wherein determining the temporal distribution comprises separating the candidate phrases into groups based on a time stamp.

3 . The method of claim 2 , wherein separating the candidate phrases into groups, comprises groups having a uniform number of candidate phrases.

4 . The method of claim 1 , wherein determining interestingness of each candidate phrase comprises:

scaling each candidate phrase frequency across the temporal distribution and computing the average of those scaled values or,

determining a coefficient of variation of the temporal distribution for each candidate phrase.

5 . The method of claim 1 , further comprising simplifying the candidate phrases by removing excess words after determining interestingness of the candidate phrases.

6 . The method of claim 1 , further comprising:

determining the correlation of the candidate phrases; and

merging the correlated candidate phrases.

7 . The method of claim 6 , further comprising removing merged candidate phrases below a predetermined threshold.

8 . The method of claim 1 , wherein displaying the candidate phrases further comprises providing the candidate phrases to an operator by an interface having at least one control for at least one metric of the candidate phrases.

9 . The method of claim 8 , further comprising determining the relevance to an operator selected candidate phrase.

10 . The method of claim 9 , wherein determining the relevance comprises determining a correlation between the candidate phrases and the operator selected candidate phrase.

11 . The method of claim 10 , further comprising determining the interestingness of the candidate phrases correlated to the operator selected candidate phrase.

12 . The method of claim 11 , further comprising displaying the highest correlated and the most interesting candidate phrases to an operator.

13 . The method of claim 8 , further comprising

altering at least one metric of the candidate phrases; and

altering a visual cue indicative of the displayed candidate phrases within the interface.

14 . A non-transitory, computer-readable storage device containing software than, when executed by a processor, causes the processor to:

extract a plurality of candidate phrases from a content stream;

exclude the candidate phrases occurring below a minimum frequency within the content stream;

group the candidate phrases in a temporal distribution according to an associated time stamp;

determine the interestingness and correlation of each of the candidate phrases; and

simplify the candidate phrases and

merge the candidate phrases;

wherein the determine the interestingness and correlation of each the candidate phrases comprises statistical analysis of the extracted candidate phrases.

15 . The non-transitory, computer-readable storage device of claim 14 wherein the software causes the processor to group the candidate phrases in equal sized groups.

16 . The non-transitory, computer-readable storage device of claim 14 wherein the software causes the processor to:

scale each candidate phrase frequency across the temporal distribution; or

calculate the variation of the temporal distribution for each candidate phrase by the ratio of the candidate phrase frequency standard deviation to the candidate phrase frequency average;

to determine the interestingness of each candidate phrase.

17 . The non-transitory, computer-readable storage device of claim 14 wherein the software causes the processor to:

calculate the product of the frequency of each of the candidate phrases within a temporal group and frequency of each of the candidate phrases within the temporal distribution; or

calculate Pearson's Coefficient of Correlation;

to determine the correlation of each candidate phrase.

18 . A system, comprising:

an extraction engine to generate a set of candidate phrases from a content stream with temporal resolution and exclude candidate phrases having a frequency below a threshold;

a distribution engine to distribute the candidate phrases into a plurality of groups based on the temporal resolution of the candidate phrases; and

a condensing engine to simplify the candidate phrases by the interestingness and the correlation of the candidate phrases, wherein the condensing engine excludes one portion of the candidate phrases and merges another portion of the candidate phrases.

19 . The system of claim 18 , wherein the distribution engine distributes the candidate phrases such that each of the plurality of groups has an equal number of candidate phrases.

20 . The system of claim 18 , wherein the condensing engine merges a portion of the candidate phrases based on the correlation of the candidate phrases.