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Preventing Travel Review Fraud with Semantics

A recent article reports, “As publishers, consumers and law enforcement get more sophisticated, so will the bad guys. It is doubtful fake reviews can ever be fully eradicated. The problem is that even amateur FROs realize that encouraging positive review posts about an establishment only goes so far… Those electing to go negative on competitors can be problematic.”

It continues, “One of the primary criticisms of TripAdvisor is that it provides a homogenized perspective of the hotels – it provides many filter criteria to trim down the hotel list based on various criteria, but the filters are property-centric and the new result set includes the same list of reviews. Reviews may only be filtered by family/couples /business to reduce the number of reviews to scan. While the Facebook integration definitely helps provide perspectives of trusted friends, there are opportunities to apply more semantic and collaborative analytical processes to produce more relevant reviews.”

It adds, “Every traveler essentially seeks the same result – the hotel that represents the best experience/price ratio, based on the specific needs for a particular itinerary. But it needs to go further – it’s all about context. Does a hotel match an individual’s sense of style? Does it match up favorably with other hotels the guest liked when traveling on a similar itinerary? Providing answers to these questions not only provides a much more relevant hotel recommendation, but also introduces sufficient nuance to frustrate even the most accomplished FROs. The solution is to enable a more semantic and persona-based context into the hotel reviews that may be considered when ranking candidate hotels. Applying semantic search processes should greatly assist travelers by organizing the daunting amount of text provided by an ever growing army of reviewers.”

Read more here.

Image: Courtesy Flickr/ chinnian

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