The Timing of Words

The Timing of Words

Problem being addressed

Semantic relatedness is an important topic for applications that involve document searches. However the use and context of words has a temporal component​,​ and meaning tends to change with time. What approaches can be taken to understand and model this?

Solution

Temporal semantics and dynamics involves understanding the change in relationships between words over time. Words like war and peace for example, tend to become more "related" during wartime; think news headlines. In order to understand dynamically changing semantics, a time based model for word relationships is developed in the paper. The basic idea is to represent individual words as static concept vectors; extract the temporal dynamics for each concept and to scale each concept's time series according to the weight or importance of the concept. Thus, the changing weight of the concept with time can account for the dynamics of word relatedness.

Advantages of this solution

This is the first attempt to tackle the problem of the changing meaning and relatedness of words with time. It has important applications in search and other areas involving language.

Solution originally applied in these industries

internet

Internet Industry

Possible New Application of the Work

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Advertising Industry

Word context could have interesting applications in the advertising industry because different groups of people tend to use words in subtly different ways. Understanding how people use words, is key to communication, and communication is key to advertising.

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Education Sector

Educators and students have a tendency to use words differently from each other. Perhaps an application of this research could be to understand the evolution of an individuals word cloud and language with time. This could help with language education, for example.

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Entertainment Industry

An interesting application that may have minimal commercial value, would be to study the evolution of language in film. We use words very differently today than we did in the 1960's and an understanding of how words were used in that time, could give key cultural indicators. It may also make for historically accurate movie scripting.

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

Management Sector

An application to management could be to understand the differences in jargon between different groups in the workplace. This would include the differences in language between staff and management of course. How people use language is connected to how they think and problem solve, so there is a lot to be learned, and taught.

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