Should I post this method on this sites feedback forum and will this method help you?

After combing the algorithms from any search engines, I got this search algorithm-

Which filters on Fresh and Complete Information Gathering Quality Experience with Relevance

In this algorithm, all the sentences of different posts classified and weighted in the format below.

Amount of information provided- The Usefulness of its known facts and Knowledge secretly known to be correct -Article Sentiments such as all-inclusive sentiment value of an article(Positive, Negative and Neutral) - Usage of the knowledge and the Question and Answer Pairs of the information-Common Queries for which the information is showable for-Disabigunated Entities

And after this set of computer instructions will mark and weight the

Documents, (Series of words that make sense and that have a subject and a verb), and Phrases with the following factors -

  1. Information Quality

  2. Useful

  3. Calls for/uses Feelings(Especially Positive)

  4. Helpful

  5. Hard Words words used

  6. Consistency and, frequency of (completes/goes along with)(Should not be above a certain (dividing line/point where something begins or changes) to suffer a decrease in weight)

  7. Cause and Solution

  8. (reported or said to be)(or Reputation)

  9. Post Usability

  10. Post Engagement

  11. Freshness

  12. (quality of being connected or related to something)

  13. Post Quality

  14. Relevancy

  15. Information Demand

  16. Forum Click Rate

  17. Rarity of Content

  18. Efficient usage of user resources

  19. Acceptable Overall Value

After the user provides a search question to the Search engine of his search question will be (pulled out or taken from something else) and compared with similar entities.

Then the main keyword from his question will be (pulled out or taken from something else) after which another version of his keyword and (related to the meaning of words) Keywords created from his search question and then compared with the documents in the search engine and the terms which the user is interested in will be be given an increase in weights(The user can specify his interests by or they can be detected by an algorithm)

The weights of search results that contain rare words and terms which are useful and helpful to the question will increase, Those unusual words which are related to plentiful and usual words by counting the frequency of the rarest words and phrases both among each other and also the whole document in which they appear while preserving the Topic name in the forum post

And it is likely that by this the algorithm will find words which will lead this algorithm to find documents that are related to each other but contain letters that have more than one meaning and are rare and the hit/effect of this factor can increase when the “Pages I have viewed” filter is activated using synsets such as (“Hullo” will further improve the accuracy of this algorithm)

And Information fitness is the value which an information gives to a user,

And in this part of the algorithm,

1 The text of the highest weighed forum posts of different categories of questions that can be asked will be compared to uncommon user question parts

2 To find similarities and complete the searcher’s information finding with new information that is similar to the knowledge returned by the search query of this algorithm.

  1. Which is then tweaked that(with the content of the attributes of the (clearly connected or related) entities and then the (dis ambiguities entities are searched(from the same highly weighted documents but this time the threshold for getting filtered is lowered)
  2. And those forum posts that had initially failed to get a rank but were later ranked because they added something new and are relevant are reranked.

The Question and Answer Pairs are understood by meaning,

As some search engines take the meaning of the text into account.

Further Thoughts

Predicting Clickthrough data by taking peak visiting rates of websites while factoring important events and website reputation and its information demand into account with the historical data of the usage of the algorithm given above along with conditional selective attention will cause this algorithm to be much more useful

Insight which I gained by thinking about this algorithm

  1. Forum posts which contain Title(s) along with their content which the user is looking for according to his question provide more helpful and useful knowledge are better especially if they contain well-written quality thoughts and.

Insight of the Page Rank algorithm (Search based on Relevance)

  1. (clearly connected or related) Websites Link to (clearly connected or related) Websites.

Credit to Google for information about their Page Experience algorithm that made me add the usability factor in this forum post and also to Bing for telling probably most of their set of computer instructions in an interview of their search engine website.

Important Note

Some of the algorithms which I have talked about/said here may be pated or may about to be patented,

I request you to give suggestions to make this algorithm better and faster so that it may be used by people and I ask people those who want to find whether this idea is covered by a patent of Google, Yandex, and Bing to do by doing some Searches which I can not do as I lack the necessary knowledge to do it and if you will do this and report your results then this will help me and perhaps even others,



Well, I have edited and simplified this algorithm to avoid any patent issues and the four indexing and ranking steps of this new algorithm are -

1)Highlight Genuine and accurate Key achievements with different highlighters(For later use in Rankings.

Whenever it used, To save speed, follow the above step only once until a certain amount of time for significantly increasing the speed of the search (Can get stored in a database named Genuine and Correct achievements of article content database).

2)Identify the type of intent with main citation contents(Ex-Encyclopedia(Informativeness)

Filtering of Forum Posts

  1. Classify similar categories with different tags with goals of the topic poster(Ex- Tag(Method of Loci), Goal(Recall and Retention) )

  2. Filter based on his knowledge which can be known with about 60% accuracy by his query by query and low scores (Ex- If the searcher knows the information given in the forum post(Found out by his question) or if a forum post had achieved low scores when its keywords will be to the above database)

Can anyone tell me how well this algorithm may work for your common queries based on the information you had gained from searching in this forum and compare and compare its results with the Art of Memory forum’s search engine so that I can evaluate my algorithm,