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     Before You Drown, Let Your Computer Pre-Select

"Reading from the Internet is like drinking water from a fire hose. If you don't know how to do it, in the end you are wet all over. But you are still thirsty!" This adage is particularly true for those people who have to do a lot of PROFESSIONAL reading. With so much information on the net -- some useful and some not -- you simply can’t absorb everything. You must discriminate in what you spend your time on. You must begin by selecting those items that are relevant to your interests -- then categorize them and deal with them accordingly. 

Notice the word 'select' above. I didn't say READ -- for a reason. In order to select or categorize a text you are not required to read it -- you don't even have to look at it. Let the computer 'E-READ' it for you. If the outcome indicates that an article is worth reading yourself, you can still do that. But it has taken you much less time and effort to separate the wheat from the chaff.

E-reading begins when you prepare a list of KEYWORDS that are likely to appear in those texts that interest you. If you want to make your e-reading more selectively, you can assign different 'WEIGHTS' to your keywords. Keywords that might indicate a highly relevant text are assigned a higher 'weight'. In e-reading, the computer compares the text, word for word, with each of the keywords. If they match, it's a 'HIT'. Weights of all 'hits' are added up. As a result of e-reading, the 'total weight' of each text is displayed. 

However, the relevance of texts cannot be gauged by a linear scale alone. One kind of text might always interest you. Another kind of text might be interesting only if the author ALSO addressed certain specific points. In the end, a text may come out at a fairly low 'total weight' -- but you might miss the boat when ignoring it because of it’s RELATIONSHIP to other content.

The determination of ‘weight’ is also complicated by the fact that some authors seem to take it as a challenge to their creativity to come up with the most fanciful titles possible. To the reader, the title might be not very meaningful -- or may even be MISLEADING. And then there are those texts that cannot have any meaningful title, such as resumes. It's always a good idea not to rely solely on the 'total weight' resulting from an e-reading, but to have a look on the title (if there is one) and perhaps the first few lines.

The context in which the keywords were encountered might also give you an idea of the contents. Therefore, a good e-reading tool like 'eRead' displays not only the text statistics but also the keyword in CONTEXT. All the lines in which one or more keywords were found is displayed, along with the sum of weights of the line. For the user, a peek into the keyword in context list can reveal a great deal of information about that text.

Still, that's not the final word on sorting. If you have to select among hundreds of texts per day, you will not be happy looking through a huge random list based on keywords. So, 'categorization' was introduced. To keep it user-friendly, keywords are lumped together according to a pre-assigned HEADING. For example, the keywords ‘leaf’ and ‘pest’ and ‘fertilizer’ might be included in the heading ‘gardening’. 

In the text statistics resulting from e-reading, the category with the MOST 'hits' is displayed along with the PERCENTAGE of total hits. With a good keyword list broken into 10 categories, a ‘suggested category' that has about 40 to 50+ % of total hits deserves a closer look into the text. But if it has much less than 40% of the hits, the text might be less than relevant to your needs. Do keep in mind that, with more categories, the percentage of hits per category will be smaller.

There are a number of other text statistics that are helpful to the user. In a very lengthy text, the 'total weight' would be surprisingly high, and therefore not particularly telling of its value. In such a case a savvy user would intuitively have a look at the 'hits per LINE'. If that number is far below 1 hit per line, the seemingly high 'total weight' came about simply by amassing a hit now and then. For very short articles, this number can even offset a seemingly low 'total weight'. 

'Hits per CATEGORY' is another useful text statistic. For all categories in your keyword file, the number of hits is displayed. This seems to be unnecessary, if you get a 'suggested category' with a high percentage -- one that clearly stands out among the other categories. But if you have a number of categories with fairly equal percentages, you won’t want to simply focus on the one category that was selected as the most popular. Quite a different category might have had only one or two fewer hits. 

Have a quick look at 'hits per category'. If the percentage of the 'suggested category' seems low, you should consider COMBINING several of your categories. If that percentage is significantly high, it could mean that you choose the wrong categorization. Your best bet will be to try it on some other texts of your collection. Keep in mind that this system is only as good as the STRUCTURE you give it. It can only make choices for you if you input good information up front. It might be that you have a text you initially feel is appropriate and relevant for the subject you are researching. But after e-reading it, the text statistics are not so impressive. Your first thought should be. 'What could I do to strengthen the SELECTIVITY of my keyword list?'

If this sounds like an intriguing way to cut DOWN on your internet reading, try it yourself! Download a free 30-day demo version of 'eRead' from www.1st-components.com/free.htm.


Gunter Gerdenitsch is the owner of '1st Components Design', Universal Software Components for Computer Applications without Programming. He is the specialist for everyday use of the computer relating subjects of e-business, "Living in times of the Internet", etc. Visit his website at www.1st-components.com or email him at .

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