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"description": "# Concept-Search\n\n[](https://github.com/ItsSiddharth/context_search/blob/master/LICENSE) [](http://makeapullrequest.com) \n\n## For source code \nThis the my Github repo. \nContact me for support and PRs are welcome.\n\n## Usage \n1. Pip install the package.\n```\n$ pip3 install smart-search\n```\n* **NOTE** : Please have the pickle file in the same folder as the python script in which you will use our pip package.\n\n> Here i use the glove.6B.zip file from Standfords Github repository from the hyperlink.\n\n## Syntax \n1. Import the library.\n```\n>> import smart_search\n```\n2. Create an object of the class, smart_search.model(). Say, `functioncaller`.\n```\n>> functioncaller = smart_search.model()\n```\n3. Now to convert a pdf to a list of lists containing page.no and words after stop word removal, we use the built in function `getting_list_of_words()`. This accepts 1 argument, i.e the path to the pdf and returns the required list to be fed to the model.\n```\n>> pdf_list = functioncaller.getting_list_of_words('path to your pdf')\n```\n4. Pass this list to the model along with the word you want to get the search result of using the `perform_skip()` function. This accepts 2 variables, i.e the list produced by the previous function and the word you want to search for and retuns the top 5 relevant search locations of the word you searched for.\n```\n>> location[0:5] = perform_skip(pdf_list, input_word)\n```\n5. You can use subprocesses library of python to navigate to the page if you want to.\n\n## LICENSE\nMIT\n\n\n\n\n",
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