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A previously created thread on this topic was closed in the meantime. I would suspect that the reason for this was that the yield of such a search has not been recognized or appreciated sufficiently. A faceted search is characterised by the fact that the user gradually reduces the number of search results by adding keywords that have been used in the results. For this purpose, the system displays the keywords whose inclusion would not reduce the result set to an empty quantity. Such a procedure proves to be extremely effective in discriminating against keyword registers because the user does not have to make any assumptions about the keywords actually used, since these are provided by the system, depending on the already reduced result set. In this way, the relevant entities can usually be limited to a manageable number of hits with just a few clicks, even in very large databases. At the same time, the procedure is very simple in technical implementation. It simply consists of repeating the following steps: The number of each keyword in the observed data volume is determined and displayed. The user selects one of these keywords. Taking this into account reduces the amount of data considered. Then the number of entries per keyword has to be determined again, i. e. step 1 has to be executed again. This type of successive filtering of the data makes the yield from the information value of the allocated keywords actually accessible. Individually applied, the value of a keyword must decrease to the extent that it is applied. The more often a keyword is used, the less value it has until it becomes completely useless. The procedure is inexpensive and extremely effective. Without such a filtering method, however, systematic keywording is of no practical value. The value of keywords is only determined by their combination, to the extent that the volume of data increases. I would recommend that you re-evaluate this function. The effectiveness of this discrimination procedure is evident. In Apache Solr and Lucene there are concrete implementations which make the process tangible.
I would like to see note searching/browsing by a method known as Elastic Lists or Elastic Searching or Facet Browsing - there's a famous example on the web under "elastic lists nobel prize winners" The interface would start with a list of your Tags. You select a Tag (becomes the parent), then the Tag list is hierarch-ically narrowed to show only the Tags shared (children) with the parent Tag. The user continues to select each drill-down level of tagging. This gives you the ability to browse your notes by "pivoting" your data based on any combination of tags, and starting with any tag. It does not require a predefined tag hierarchy and allows you to browse your data elastically by whatever mood (Tag) you are in. For example, an interior decorator, or home owner might have the following tags: bathrooms curtains paint red master bedrooms chairs furniture Let's assume the user has several notes tagged with: bedrooms, master, furniture And there are also note(s) tagged with: projects, paint, bathrooms, master The user could start their note browsing by clicking on any one of these tags (just as Evernote works now). Let's say the user is in a master bedroom suite enhancement mood. But they don't know what they want to do yet, they just want to browse notes related to this area of the house. So they click on "master". The not-existing-now browsing feature would then only display the resulting Tags that are shared with the parent Tag. The user then sees Tags for "paint, projects, furniture, master, bedrooms, bathrooms" in a hierarchy order indented under the parent Tag. User then selects, "paint" because they are in a painting mood... the resulting list of shared Tags is then limited no deeper because there are no more shared tags. Why this method of browsing? Let's say next weekend the user is in a furniture buying mood, but they just want to browse notes in general and let the possibilities unfold organically for inspiration from their notes database. I realize you can select multiple tags at once, but if you have 1000's of notes, or hundreds of tags, you don't always know what tags are shared with others. Also, this assumes you KNOW in advance what you want to see - perhaps you just want to be INSPIRED by the notes you have collected over the years for this very day years later. I have other day-to-day examples of this pivoting or elasticity that we encounter, for example an employee manual. The employee can click on "sales", then see related Tags "introductions, scripts, leads, fabrics"... but they could also have started their drill-down with "fabrics" depending on what they are searching for. - sorry this was a little hard to explain by text example only. I'll be glad to explain in more detail if there is some curiosity as to how or more examples of why.