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Semantic search in Media

13.03.2011

Semantic technologies, or the study of meaning, will play a big role in the further development of knowledge base management for many industries, especially for the media industry.
Semantic search engines represent a wide area and a higher realm of semantic technology, which also includes a knowledge base, finding and interpreting information, and so on. The main goal of semantic search data is to obtain greater accuracy of results, so the system difficult to understand the intentions of the person and contextual relationship between terms used in searches.





News media

All serious web sites that providing news attract more visitors. This is especially true for news organizations and blogs, which produce a large amount of news and comment every day, so the news is not much helpful in this piles because no one will read. So the goal is to make content that can be searched as much as possible.
The main challenge in information retrieval is the structure of the web, which is predominantly written in HTML, which is used to show how it will look like the information and not what it means. As a result we have the information within a web page such as captions, date of publication that are formatted within the HTML but are not explicitly marked. This is a difficulty the rest of the web to understand the nature of structured content. This is because they are formatted web page that people can easily read them, and machines can not easily follow the meaning, if there is no consistent structure.
Many communities on the web are working on this problem, especially Linked Data, which is all the more the center of these efforts. Linked Data is the best example for publishing, sharing and connecting pieces of data, information and knowledge in the Semantic Web.

Social Media

Social media is another area where Web data looks powerful. For example Twitter, which has 110 million messages per day and 250 million active Facebook users per day, looks like a great platform to advertise a brand.
Users spend more time on social networks, and companies understand the importance of the presence of their brands on social platforms. Analysts have focused on the adaptation of this advertising medium, while companies are trying to measure return on investment - ROI of marketing activities on social networks. In all these activities the analyst tools are of major importance.
Following the trend of last year, many companies have added the analysis of public opinion (sentiment) in the list of must-have features in their tools for monitoring social media.
There are two-way communication of a brand on social platforms, the first when the brands marketing message sent through social channels, the other when users discuss brands and products. As a result there are two main ways in which brands are currently using semantic technology:
- Consumer sentiment analysis (public opinion). Brands (companies) want to know what consumers are talking about them. Using text analysis and a growing number of services that analyze the grammar and find the meaning behind some
sentence that he or she writes about a product. In most cases, this means determining the positive or negative opinions about a product or service. In other advanced cases, is going to find the intention behind some statements (sentences). These services enable brand companies to separate the unimportant events of the social networks of those with the greatest potential gain.
- The consistency of marketing messages. By monitoring the mood of users is obviously important, but there is another application of text analysis in social networks, and this is research into the consistency of marketing messages. Information that is obtained from this analysis are important for determining future brand strategies and messages.




Posted by: Dejan Petrovic