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I am curious as to the experience of others with regard to their experience with natural language stemming for site indexes. I ask this as I am in the process of rewriting a site search engine (to improve maintainability and to fit the corporate application environment) and have could across a number of discussions regarding natural language stemming in this type of application.

For those unfamiliar with this concept, stemming is the process of reducing a word to its stem or root form - This allows similar words such as computer and computing to be conflated or reduced to a single root (for example, comput), thereby reducing index dictionary size and in theory, reducing storage requirements and processing time - A further discussion on this concept can be found here.

While this type of processing allows for reducing index dictionary keys, I am concerned about he likelihood for stemming errors whereby dissimilar words may be stemmed to a similar root, particularly given that indexing speed and space requirements should not be an issue in the application environment - See here for a discussion on over- and under-stemming errors.

And so I ask a barage of questions:

  • What are the experiences of fellow monks with natural language stemming?
  • Have other monks found better results, as measured by minimal stemming errors, via one stemming algorithm (for example, Paice-Husk, Porter, etc.) over another?
  • And in particular, what are other monks experiences with the Porter algorithm of stemming implemented in Lingua::Stem?

My thanks in advance


In reply to Natural Language Index Stemming by rob_au

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