Research Article
Anomalous Behavior Detection Framework Using HTM-Based Semantic Folding Technique
Table 14
A sample from Yelp dataset as processed.
| | S.no | Text | Predicted | Actual category | Actual |
| | 1 | “Wow loved this place” | 1 | BC | 1 | | 2 | “Crust is not good” | 0 | A | 0 | | 3 | “It is not tasty and the texture was just nasty” | 1 | BC | 1 | | 4 | “Stopped by during the late may bank holiday off Rick Steve recommendation and loved it” | 1 | A | 0 | | 5 | “The selection on the menu was great and so were the prices” | 1 | BC | 1 | | 6 | “Now I am getting angry and I want my damn pho” | 1 | BC | 1 | | 7 | “Honestly, it did not taste that fresh” | 1 | BC | 1 | | 8 | “The potatoes were not fresh and like rubber and you could tell they had been made up ahead of time being kept under a warmer” | 1 | BC | 1 | | 9 | “The fries were great too” | 1 | BC | 1 | | 10 | “A good great touch” | 1 | BC | 1 | | 11 | “Service was very prompt” | 1 | BC | 1 | | 12 | “Would not go back” | 1 | BC | 1 | | 13 | “The cashier had no care whatsoever on what I had to say it still ended up being way overpriced” | 1 | A | 0 | | 14 | “I tried the cape cod ravoli” | 1 | BC | 1 | | 15 | “I was disgusted because I was pretty sure that was human hair” | 1 | BC | 1 | | 16 | “I was shocked because no signs indicate cash only” | 1 | A | 0 | | 17 | “Highly demanded” | 0 | A | 0 | | 18 | “Waitress was a little slow in service” | 1 | BC | 1 | | 19 | “This place is not worth your time” | 1 | BC | 1 | | 20 | “Did not like at all” | 1 | BC | 1 |
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