An anomaly detection apparatus, method, and computer program product are provided using a probabilistic latent semantic analysis (PLSA). In use, data is received, and a PLSA is performed, based on the data. Further, one or more anomalies are detected in the data, based on the PLSA. Still yet, information identifying the one or more anomalies is stored and/or displayed.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer program product embodied on a non-transitory computer readable medium, comprising: code for receiving data; code for performing a probabilistic latent semantic analysis utilizing at least one processor, based on the data; code for detecting one or more anomalies in the data, based on the probabilistic latent semantic analysis; and code for displaying information on the one or more anomalies. 2. The computer program product of claim 1, wherein the computer program product is configured such that the probabilistic latent semantic analysis includes a Gaussian probabilistic latent semantic analysis. 3. The computer program product of claim 1, wherein the computer program product is configured such that the data is received in connection with at least one of a cellular network, one or more base stations, or one or more user devices. 4. The computer program product of claim 1, wherein the computer program product is configured such that the data is received in connection with one or more radio network controllers. 5. The computer program product of claim 1, wherein the computer program product is configured such that one or more first variables associated with the data are mapped to one or more second variables associated with the probabilistic latent semantic analysis. 6. The computer program product of claim 5, wherein the computer program product is configured such that the one or more first variables include a time variable. 7. The computer program product of claim 5, wherein the computer program product is configured such that the one or more first variables include a space variable. 8. The computer program product of claim 5, wherein the computer program product is configured such that the one or more first variables include a network node or user equipment variable. 9. The computer program product of claim 5, wherein the computer program product is configured such that the one or more first variables include a key performance indicator variable. 10. The computer program product of claim 5, wherein the computer program product is configured such that the one or more first variables include a key quality indicator variable. 11. The computer program product of claim 5, wherein the computer program product is configured such that the one or more first variables include a network resource variable. 12. The computer program product of claim 5, wherein the computer program product is configured such that the one or more first variables include a network traffic variable. 13. The computer program product of claim 5, wherein the computer program product is configured such that the one or more first variables include a location variable. 14. The computer program product of claim 5, wherein the computer program product is configured such that the one or more second variables include co-occurrence variables. 15. The computer program product of claim 5, wherein the computer program product is configured such that the one or more second variables include a cluster variable. 16. The computer program product of claim 1, and further comprising: code for setting one or more thresholds. 17. The computer program product of claim 16, and further comprising: code for identifying potential anomalies based on the one or more thresholds. 18. The computer program product of claim 16, and further comprising: code for confirming the one or more potential anomalies to be anomalies based a time in which the one or more potential anomalies persists. 19. A method, comprising: receiving data; performing a probabilistic latent semantic analysis on the data, utilizing at least one processor; detecting one or more anomalies in the data, based on the probabilistic latent semantic analysis, utilizing the at least one processor; and storing information identifying the one or more anomalies, utilizing memory in communication with the at least one processor. 20. An apparatus, comprising: at least one processor configured for: receiving data; performing a probabilistic latent semantic analysis, utilizing the data; detecting one or more anomalies in the data, based on the probabilistic latent semantic analysis; and causing output of information identifying the one or more anomalies.