Semantic Wranglers to Tame Media Content
February 6, 2012
When the prolificacy of the media scape overwhelms, it is semantic technology to the rescue. So declares ReadWriteWeb in “Semantic Tech the Key to Finding Meaning in the Media.” Writer Chris Lamb maintains that today’s deluges of information have made attention span the prize, and delivering relevancy the key. Strategies have included tapping readers’ social graphs, profiles, and preferences to filter news content. Lamb writes:
These current approaches are doomed. With respect to social graph curation, people have different roles at during different times. On the weekend, a reader might be interested in arts, entertainment and sports news based on a friends and family. During the week, this same person may be interested in business news based on recommendations from trading partners in the capital markets. How do readers seamlessly reconcile this?
Lamb doesn’t have the answer, but says he does know what technologies will underlie the eventual solutions: tagging, semantic extraction, disambiguation, and linked data structures (including cloud data). See the write up for more the reasoning behind each.
Semantic technology can perform useful functions. Rich media pose some special challenges. Among them are the issues of data volume and available processing power, latency, and variability in indexable content. What about a silent movie? What about a program which features interviews with individuals with a substance abuse problem who speak colloquially with a mumble?
Cynthia Murrell, February 6, 2012
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