W3C Semantic Web Activity

The requirement of information is inestimable and the more you acquire the more you would like to get. Information is the very much to information decisions. It is the natural truth that human being have never stopped thinking and never tired of achieving any thing. As we gather more information we want to gather more information to have better knowledge.

In the world of internet, it has emerged as a powerful source of information that has the potential to quench our hunger for information. Therefore, searching for information in this huge database is an overwhelming job. The launch of Search engine optimization had solved these overwhelming tasks and made the already available information more accessible without any hard work. However, can a Search engine optimization identify a human query like a human being? Can they recognize and tell with accurateness, if anyone wants to search ‘mango’ for a fruit? Let’s set upon a journey to find out if they can.

Latent Semantic Analysis (LSA) is a methods engaged in natural language processing, for analyzing relationship among a group of documents and the terms they enclose, by generating a group of ideas related to the documents and terms. The purpose is to discover symmetry in formless data and use these patterns to offer more efficient search and classification.

Previously keyword density got high ranked on almost every Search engine optimization optimizer’s program. Every Search engine optimization experts had shown there approval that the keyword density per page should 2%-7% on every page. But after the arrival of LSI, keyword density has lost its significance in comparison to previous importance.

Now the importance now lies on relevant and related words and phrases and their repetitions with the page. Related terms, synonyms, acronym and phrases which can be utilized to set up the topic, context and theme of any of the page will leave a significant impact on how it is recognized by top Search engine optimization . The significance of theme words and phrases would unquestionably have a vital role, as more and more search engines niche in LSI or piece of the thought in their ranking algorithms.

Latent Semantic Analysis is often not recognizing its accurate reason since of the mathematical difficulty concerned in making it job. Vector space model, the idea at the back Latent Semantic Analysis engages involved calculations and perceptive. Though, this fact must not dispirit someone since the thought is to recognize its bang on Search engine optimization rankings and not on how it is applied.