Huge amount of different types of information are being posted on the web on a daily basis; therefore, searching capabilities should be provided to help users in finding their requested information. Locating a specific type of information within large repositories of disparate data becomes difficult, if not impossible, without specialized information retrieval systems. Traditional or text-based search engines do not achieve the level of success that users seek in retrieving structured information (e. g. mathematical information). For example, when a user searches for x(y+z) using Google, Google retrieves documents that contain xyz, x+y=z, (x+y+z) =xyz or any other document that contains x, y, and/or z, but not x(y+z) as a standalone expression. The reason behind this is that Google uses the text-based search capabilities/ Algorithms that depend, mostly, on techniques for matching and probabilities of occurrences of x, y, and z. The major obstacle of math search in current text search systems is that those systems do not differentiate between a user query that contains a mathematical expression, and any other query that contains text terms. Therefore, those text-based search systems process mathematical expressions as other texts, regardless of its nature whether being well-structured or not. Here in this context, the text search process will be refined to be applicable in searching for a mathematical expression by implementing a system that is responsible for detecting equivalent math expressions. In fact, more algorithms will be added to the Information Retrieval System in order to make it suitable to do search for a mathematical expression as well as other forms of text.

Math Search Expression's Equivalent Forms Mathematical Expression Detecting Equivalency Grammar Text-based Search Systems