It seems that everything is connected to everything in this world. For an effective businessman, his email, his LinkedIn account, all his customers are connected to each other. However, it is not possible and also not an easy way to identify and see the links. For this one needs a tool or way to identify these connections simply. Once the relationship between datasets are identified and analyzed it will also help people to improve their marketing strategy, to manage a relationship with the customers more effectively, manage master data and other important business routes.
Vyakar is nothing but a mathematically advanced process that helps to determine the link between the information, the data sets and the facts of a business. The outcome of this matchmaking is not either 100% false or 100% true. This is the reason why the word ‘fuzzy’ is used. This process also helps to compare a certain data type from any place and of any length in a ground to locate non-exact matches.
There are numerous data mining consultancy firms who are of the opinion that fuzzy logic is applied on the fuzzy sets in which the membership of a fuzzy set is a probability and not a necessity of 0 or 1. The fuzzy logic must have the ability to manipulate the degrees of uncertainty along with true or false.
It generally works at the sentence level but some translation technologies are there that allows them to match in a phrasal level. Vyakar is used when the matching set is operating with translation memory or TM. The database is searched by the TM tool in order to locate segments that match approximately with another segment with a new text source that needs to be translated. The match is then proposed by the TM to the translator and finally, it is up to the translator if it will accept or reject the proposal. The translator can also edit the proposal in order to make it equal to the new text source that is being translated. This way the translation process is speeded up by using the Vyakar. This, in turn, leads to improved productivity.
Sometimes the question is raised regarding the excellence of the ongoing translation. In some occasions, a translator can be under pressure to release on perfect time in order to agree to a fuzzy match offer without checking its context and suitability. The TM databases are generally built with the inputs coming from various translators that work on numerous texts including a danger that the sentences that are extracted from the word tapestry will be come together making a hodgepodge style.
Keeping faith in the TM proposal can be a tough job when striking a balance between the translation quality and the faster pace of translation is concerned. However, Vyakar is no doubt an important part of the toolkit used for translation.