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  1.  
  2. Searching and Sorting Algorithms Report Guide
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  4. Real World Application of Searching Algorithm
  5. Example 1:
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  7. Arguably one of the biggest uses for Searching and Sorting Algorithms are search engines. Search engines like google use specialized algorithms so that people can find what they need fast and accurately. For example when you search ‘Real world Application of Searching Algorithm’ google’s search engine will look across the web for web pages with the keywords real, world, application, of, searching, algorithm. Then it will rank the pages on how many keywords relate, the popularity of the website and the compatibility. One way Google makes this process a whole lot faster is within seconds of you uploading your new web page google has categorized it on description, keywords, tags, navigation etc.
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  9. Example 2:
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  11. In movie cinema’s you search for your pre booked seat based on Rows (Alphabetical Order from A to Z (A at the bottom of the cinema Z at the top) and Seats in the row by number (1 on the left through to how many seats to the right) This system ensures that everytime can find their seat quickly and easily. Additionally this is used in planes to seat passengers however it’s usually the opposite so numbers are rows and letters are seats. And most airlines board the passengers back to front so that everyone can board quickly, easily and without hassle.
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  13. Purpose of Searching Algorithms:
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  15. Searching Algorithms so that the user can find a specific thing faster. Imagine that you’re in a library and trying to find a book on Economics but you have no idea where to look at how to look so you start at one end of the library and check every single book. This would take hours if not days. Searching algorithms can come in handy because they will use an algorithm to locate where an item or thing is then relay the data to the user. E.g in library’s you search for a book by the first 3 letters of an author's name. So a searching algorithm can easily locate the first 3 letters of an author's name on the specific book they want then use the presorted system to search for it.
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  17. Real World Application of Sorting Algorithm
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  19. Example 1:
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  21. When a new library book comes to the library it’s manually sorted and categorized in Nonfiction (True)  and fiction (Not true). Non fiction books are categorized in the Dewey Decimal System.  000–099, general works; 100–199, philosophy and psychology; 200–299, religion; 300–399, social sciences; 400–499, language; 500–599, natural sciences and mathematics; 600–699, technology; 700–799, the arts; 800–899, literature and rhetoric; and 900–999, history, biography, and geography. And fiction books are usually sorted by the first 3 letters of the author's name. So the books can be easily found and accessed. Similar sorting systems are used all around the world.
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  23. Example 2:
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  25. Chronological sorting systems. Sorting by chronological order is basically just sorting in order of which the events occured. For example historical events on a timeline are placed in chronological order starting with the oldest event and leading to the latest one. The chronological order is commonly used because it’s a simple way that events, things and people can sorted. The user can easily look at a chronological sorting system while searching for their event, item etc and quickly find it.
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  27. Example 3:
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  29. Another extremely common sorting system is sorting by last name. For example most schools organise and sort their students on the roll call by last name e.g someone name John Smith would be called before someone named John West. This sorting system uses the alphabetical system to easily organise students names. A further example of this sorting system is in company file systems. Clients are typically organised by last name so their file can be easily accessed
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  31. Purpose of sorting algorithms:
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  33. The main purpose of a sorting algorithm is to make it easier to find something. Sorting is ordering items in a certain way to make it easier for the user to find a certain thing. Sorting algorithms are also extremely beneficial to use in conjunction with searching algorithms. Let’s take a binary searching algorithm. The binary searching algorithm looks for a number by splitting a ordered data set in half if the number it picked is too low or too high compared to the number it’s looking for. This searching algorithm doesn’t work unless the data is sorted. Many searching algorithms around the world only work and take use of sorted data. (Most of my examples show this)
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  35. Relationship Between Searching and Sorting
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  37. Searching and sorting systems usually come hand in hand. Like I previously explained in the paragraph above searching systems typically take sorted data and search for the desired output. Most searching systems  work on sorted data because it’s extremely easy to read and make use of. E.g the binary searching algorithm wouldn’t work on unsorted data nor would library searching, cinema searching and it would make google's search engine slower since it searches in their presorted data first.
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  39. Algorithm Investigation
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  46. Investigate two different searching algorithms or two different sorting algorithms. Determine the best, average and worst-case costs of each algorithm that you have selected.  Investigate the effects of cost of the two different algorithms with different data sets (e.g. different size, sorted vs unsorted, inverse order). To help you understand cost, think of it as ‘how many operations’ and that ‘how many comparisons’ is a reasonable way to measure ‘how many operations’.
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  48. Bibliography
  49. https://www.quora.com/What-is-the-purpose-of-sorting
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  51. https://neilpatel.com/blog/how-google-search-engine-really-works/
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  54. Hints
  55. Evidence:
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  57. In your evidence, describe what you understand about the cost of the various algorithms that you have demonstrated.
  58. Compare how this changes as the size of the sample increases and how this may change for different algorithms. You may choose to graph the data gained from various tests on different data sizes that you have carried out and then explain what the graph shows.
  59. Consider and discuss your understanding of best case, worst case and average case scenarios as you investigate the cost of performing an algorithm on different data sets (e.g. different size, sorted vs unsorted, inverse order).
  60. Your evidence can be shown using annotated photographs, annotated sketches, videos or a written description.
  61. Do not plagiarise any material from the Internet, particularly from Wikipedia and the CS Field Guide.
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