Both Classify and See Also make an analysis of the contextual relationships in a selected document.
In the case of See Also, the contextual relationships in the selected document are compared to the contextual relationships of each and every other document in the database.
In the case of Classify, the contextual relationships in the selected document are compared to the ‘pattern’ of contextual relationships in each and every group in the database.
“Prior use” has nothing to do with the suggestions made.
Although both See Also and Classify present a ranking of suggestions, other suggestions are presented in addition to highly ranked suggestions. I sometimes find a lower-ranked suggestion the most useful one. That’s why the algorithms don’t limit suggestions to just one. Choices are presented to the user.
I gave two examples of how documents might be filed by group in a database.
In the first, where the contents of each document within a group were filed by a topic such as Quantum Physics, it’s highly likely that the existing contents of that topical group will have a pattern of contextual relationships of the terms used in that discipline (vocabulary, frequencies of use of terms and associations among the terms present in the content) such that a newly added document about that topic will be pointed to the Quantum Physics group by Classify. Obviously, if one files documents about other topics into the Quantum Physics group, the group’s pattern of contextual relationships will be reduced in coherency, but if all the documents are topically related, the group’s pattern of contextual relationships will have high coherency, so that Classify works well.
In the second example, I gave an example of non-topical groups such as groups based on client names, rather than on the topical relationships of the contents of the group. In that organizational structure, the group named Mary Smith might contain a wide variety of topics all of which are related only by the fact that they pertain to Mary Smith. Classify will look only at the content of the documents in the group, and won’t find a highly coherent pattern of contextual relationships in that group. There’s nothing “wrong” with this approach to classification. My financial database uses a similar approach. I don’t need Classify to help me file items into such groups, as I know that, for example, any document related to Mary Smith belongs in the Mary Smith group.
Sometimes, when I’m using Classify I may decide to file a document into more than one suggested group. If I select more than a single group the document will be replicated into the selected groups. Again, there’s nothing “wrong” with this approach.
Once in a while I may find that a particular document becomes a “magnet” that makes Classify suggest a location that I don’t consider useful. For example, I once included within a database the PDF user manual for a new car that I had bought. Suddenly, Classify began suggesting the group containing the car manual for a wide range of new documents. Why? That user manual was large and dealt with a great many topics. The solution was to open the Info panel of that document and check the option to exclude it from classification.
Most of my databases are organized by topic, and I find Classify a useful assistant. Some databases are not organized by topic but by, e.g., financial transactions organized by type and date. Classify wouldn’t be useful–but I don’t need it anyway, as I already know where to file a new document in that organizational structure.
Starting out in a new database, if you are using topical groups you must first populate them with related content. As your database grows, Classify will become increasingly useful in suggesting locations for documents related to your topical groups.