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Simple search engine for articles: In this project, you will build a simple search engine that can index a set of text documents, and then
Simple search engine for articles:
In this project, you will build a simple search engine that can index a set of text documents, and then search through that indexing
Based on user queries.
Project steps:
Data collection:
Gather a collection of articles or text documents that you will use as a source of information. These articles can be from
News websites, blogs, or any other source.
Word processing:
Remove special characters, and convert all text to lowercase to standardize formatting.
Use the "Tokenization" process to break text into words or sentences.
Remove "Words Stop" common words like "and", in etc. to leave only the important words.
Use the process of Stemming or Lemmatization to convert words to their root roots.
Index construction:
Create a data structure such as "Dictionary" or "Index Inverted" to index words and link them to the documents in which they appear.
Count the frequency of words in each document to determine the relative importance of each word such as using Frequency Term or TF
IDF
Search and retrieval:
Create a simple interface that allows users to enter queries.
Analyze the query the same way you analyzed the texts tokenization stemming, etc.
Use the index to find documents that contain the words in the query.
You can use algorithms such as Similarity Cosine to rank results based on how similar documents are to the query.
Show results:
Display a list of documents that match the user's query, sorted by how closely they match.
Add additional features such as AutoComplete for queries or Suggestions.
Technology used: write codes necessary and screenshots for all processes and outputs
You can use a programming language like Python with libraries like NLTK or spaCy to process text.
To use a web interface, you can rely on Flask or Django.
To maintain the index, you can use simple data structures or databases such as SQLite or MongoDB
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