One of the most important needs of an analyst is the ability to follow changes
over time in the behavior of entities of interest. For example, a trend analysis tool
should be able to compare the activities that a company performed in some domain
in the past with its current activities in that domain. For example, a possible
conclusion from such an analysis would be that a company is shifting its activities from
one domain to another. The KDT system identifies trends by comparing a distribution of data taken from one period of time to a corresponding model distribution which is constructed from data of another period. Trends are then
discovered by searching for significant deviations from the expected model, as
before. Figure 6 lists trends that were identified across the different quarters of
the year. The program was directed to search for significant changes in the cooccurrence
distributions of Arab League countries with any other country. For example, the first line of the top listbox shows that in the 3rd quarter there was a large increase in the proportion of articles that mention both Libya and Chad among all articles mentioning Libya (from 0% in the 2nd quarter to 35.29% in the 3rd quarter). The second line shows that the proportion of such articles in the 3rd quarter was also
much higher than in the fourth quarter (a decrease over time, again to 0%). An
analyst might then want to investigate what happened in the 3rd quarter regarding Libya
and Chad. To facilitate such an investigation, the system provides access to
the specific articles that support the trend, by double clicking on the appropriate line.
Then, a listbox containing all titles of the relevant documents appears, as in Figure J,
revealing that the cause for the trend was the fighting between Libya and Chad at that
period.
Figure I - Trends in co-occurrence of Arab League countries with other countries. The
distance is measured from the period (quarter) listed in the second column (P1) and the period in the third column (P2), where each line corresponds to a large contribution to this distance. The last five columns are as in previous figures.
Finally, the user can request a graphical representation of co-occurrence frequencies
of any 2 categories, in a desired level ofgranularity of time segments. Figure K
displays the percentage of articles annotated with the category crude within the average
topic distribution of OPEC countries, across different quarters.
Figure K - Crude proportion of the topic distribution of OPEC across the year quarters
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over time in the behavior of entities of interest. For example, a trend analysis tool
should be able to compare the activities that a company performed in some domain
in the past with its current activities in that domain. For example, a possible
conclusion from such an analysis would be that a company is shifting its activities from
one domain to another. The KDT system identifies trends by comparing a distribution of data taken from one period of time to a corresponding model distribution which is constructed from data of another period. Trends are then
discovered by searching for significant deviations from the expected model, as
before. Figure 6 lists trends that were identified across the different quarters of
the year. The program was directed to search for significant changes in the cooccurrence
distributions of Arab League countries with any other country. For example, the first line of the top listbox shows that in the 3rd quarter there was a large increase in the proportion of articles that mention both Libya and Chad among all articles mentioning Libya (from 0% in the 2nd quarter to 35.29% in the 3rd quarter). The second line shows that the proportion of such articles in the 3rd quarter was also
much higher than in the fourth quarter (a decrease over time, again to 0%). An
analyst might then want to investigate what happened in the 3rd quarter regarding Libya
and Chad. To facilitate such an investigation, the system provides access to
the specific articles that support the trend, by double clicking on the appropriate line.
Then, a listbox containing all titles of the relevant documents appears, as in Figure J,
revealing that the cause for the trend was the fighting between Libya and Chad at that
period.
Figure I - Trends in co-occurrence of Arab League countries with other countries. The
distance is measured from the period (quarter) listed in the second column (P1) and the period in the third column (P2), where each line corresponds to a large contribution to this distance. The last five columns are as in previous figures.
Finally, the user can request a graphical representation of co-occurrence frequencies
of any 2 categories, in a desired level ofgranularity of time segments. Figure K
displays the percentage of articles annotated with the category crude within the average
topic distribution of OPEC countries, across different quarters.
Figure K - Crude proportion of the topic distribution of OPEC across the year quarters
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