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README.md

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 # Search_Engine
-Search Engine TIME !
+Developing a mini search-engine in python using reverse-indexed stemming and other SEOs implementations
-Inversed-Index part 1
+## Part 1: The Reversed-Index
+Create an inverted index for the corpus with data structures designed by you.
+• Tokens: all alphanumeric sequences in the dataset.
+• Stop words: do not use stopping while indexing, i.e. use all words, even
+the frequently occurring ones.
+• Stemming: use stemming for better textual matches. Suggestion: Porter
+stemming, but it is up to you to choose.
+• Important text: text in bold (b, strong), in headings (h1, h2, h3), and
+in titles should be treated as more important than the in other places.
+Verify which are the relevant HTML tags to select the important words.
+
+Building the inverted index
+Now that you have been provided the HTML files to index, you may build your
+inverted index off of them. The inverted index is simply a map with the token
+as a key and a list of its corresponding postings. A posting is the representation
+of the token’s occurrence in a document. The posting typically (not limited to)
+contains the following info (you are encouraged to think of other attributes that
+you could add to the index):
+• The document name/id the token was found in.
+• Its tf-idf score for that document (for MS1, add only the term frequency).
+Some tips:
+• When designing your inverted index, you will think about the structure
+of your posting first.
+• You would normally begin by implementing the code to calculate/fetch
+the elements which will constitute your posting.
+• Modularize. Use scripts/classes that will perform a function or a set of
+closely related functions. This helps in keeping track of your progress,
+debugging, and also dividing work amongst teammates if you’re in a group.
+• We recommend you use GitHub as a mechanism to work with your team
+members on this project, but you are not required to do so.