Collab Scholars

Abstract

Before the widespread use of digital collaborative platforms and the semantic Search engine concept, people working on projects together often had to rely on email, phone calls, and in-person meetings to coordinate and share information. This could be time- consuming and inefficient, especially for teams that were geographically dispersed or had difficulty coordinating schedules. Traditional search engines rely on matching keywords in a user’s query to documents containing those keywords, which can lead to a large number of irrelevant results and make it difficult to find what the user is actually looking for. It is difficult for traditional search engines to disambiguate the meaning of words and phrases, leading to confusion and incorrect results. Traditional search engines also have difficulty handling complex or abstract queries, leading to a lack of relevant results. Some users may not know the exact keywords to use in their search queries, making it difficult for them to find what they are looking for with a traditional search engine. Collab Scholars is a Document management and Information Retrieval system, that can be defined as the way it is used by educational organizations to manage, track and retrieve electronic documents of students throughout their degree. It’s basically a well-organized system for students to keep track of their documents with unique IDs and also a great source of knowledge with an accurate search engine that returns relevant documents even if the said documents do not contain the keywords of the query. How these Search engine works are that it uses Natural Language Processing programs such as Latent Semantic Indexing (LSI) - a concept that search engines use to discover how a keyword and content work together to mean the same thing. LSI (Latent Semantic Indexing), also known as LSA (Latent Semantic Indexing), is a technique in natural language processing of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms. LSI is based on the principle that words that are used in the same contexts tend to have similar meanings. A key feature of LSI is its ability to extract the conceptual context of a body of text by establishing associations between those terms that occur in similar contexts.