Matching resumes with job descriptions using latent semantic indexing

In this thesis, Vector Space Model of Information Retrieval is examined. First, the classical method of term frequency inverse document frequency is presented as an introduction to the problem. After introducing basics, the thesis explains the concept of Latent Semantic Indexing. Singular Value Decomposition, which is the fundamental of Latent Semantic Indexing, is explained without going too deep into Linear Algebra. Relationship between Singular Value Decomposition and Latent Semantic Indexing is also explored. Finally, thesis presents the results of its demonstration, which is matching a Resume with an appropriate Job Description by using Latent Semantic Indexing and comparing it with the classical Vector Space method.