Pointsware Instructions............................................ |
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Thank you for taking some time to look at Pointsware. This web application analyzes text to draw connections between common descriptive terms. To use the tool create a dataset plain text file like this... firetruck,red,wheels,firemen,hose apple,fruit,sweet,red,green The dataset text file can consist of any number of lines where each concept is seperated by a comma and ending with a single press of the enter key Here the primary concept is the first word (firetruck) in the comma delimited string. Each subsequent word in the comma delimited string describes the first word, the primary concept Each of the query terms entered in the interface must be a primary concept. The longer and more comprehensive your dataset is the more interesting the results of a query will be. I have chosen to employ the mutable relationships inherent in flat categorization to structure the dataset. The relationships between a primary concept and a dependent attribute only nest by one degree, and this level when interpreted by the software is flattened all the way to 0 levels of categorization. This has a benefit... in a system of textual relationships between ideas I do not want to exclude the possibility that there might be a useful textual connection between two logicaly seperated ideas. for instance... fire truck --has--> red --has--> apple There is a relationship between firetruck and apple through the common dependent attribute of red. This simple example of a compounded subject complement illustrates the basic unit of relationship the software produces. The value of this for the person working in a creative environment is that through the use of organizing relationships with this type of dataset unknown, tacitly known, and forgotten relational possibilities can be found and exploited. please look at this link to my Pointsware Blog for a more graphical example of how this works My intent in structuring the data and the file in this simple list format is to keep it easy for the user of the software, this way it is simple to maintain the file and note taking in the dataset format is some what intuitive for daily use. I have stayed away from a XML scheme for structuring relationships because of its added complexity for the user and the lack of need for more than one level of categorization. The output of the application will suffer if there are html tags, special charactors, or code mixed in it so please dont include those types of text. Also since encoding can become a problem the use of a plain text editor is strongly suggested to prevent the addition of hidden charactors in the text. I suggest JEDIT or Notepad++. One of the main reasons behind my desire to develop this piece of software is I believe short term memory is the place in thinking where conflation, interoperation, synthesizing, and invention happen. Notes on every little remotely interesting thing that occurs to me litter my pockets, desks, hard drives, and everywhere else. These pieces of paper are limited in their usefulness because of their lack of interconnectivity and their difficulty to all be completly reviewed in any expiditious manner. Even a well maintained library of indexed and tidy notebooks eventually becomes to much to look at over time. And while a library of notebooks might be useful for browsing, it is not capable of doing a targeted creative query to all of the things I have thought over the course of years. Recall of old yet related thoughts mixed with new relationships based on the current questions I am asking myself is a pattern that I have found creativly fruitful. Why wait for a inspiration applicable to your current problems to strike, when perhapse the most applicable inspiration has struck in the past. My hope for this software is that it could be used in a teaching capacity to aid students and people working in a creative environment solve problems by providing avenues to explore. |