Google Search Engine

• Technology used : Artificial Intelligence, Machine Learning , NLP ,Gen AI ,Web Development

▪ Google API Integration: Utilize the Google Custom Search JSON API to access Google search results programmatically. Use the build function from googleapiclient.discovery to create a service object for interacting with the Google Custom Search API.

▪ Natural Language Processing (NLP): Implement NLP techniques to preprocess search queries and analyze user intents. Use tools such as NLTK (Natural Language Toolkit) or spaCy for tasks like tokenization, part-of-speech tagging, and named entity recognition. Preprocessing the search queries enhances the accuracy of the search engine by understanding the user's search intent better.

▪ Generation AI (GAI): Integrate Generation AI or NLG models to generate natural language responses based on the search results. These models can summarize, paraphrase, or rephrase the search results into human-readable text, providing users with concise and relevant information.

▪ Machine Learning for Ranking: Develop machine learning algorithms to rank search results based on relevance and user engagement metrics. Train models using historical search data and user feedback to improve the ranking of search results over time. Consider features such as relevance score, user click-through rates, and dwell time to enhance the ranking algorithm.

▪ MongoDB for Data Storage: Utilize MongoDB as a NoSQL database to store user search queries, search results, user interactions, and other relevant data.