Abstract: A personalized ranking method of audio and/or video data on Internet includes the steps of locating a plurality of audio and/or video data corresponding to at least one keyword; deciding a user index by the user or picking a history behavior index if the user does not decide the user index; capturing characteristics from the aforesaid downloaded audio and/or video data according to the user index or the history behavior; comparing the captured characteristics with a user profile or a history behavior for similarity to get a similarity score; ranking the audio and/or video data according to the corresponding similarity scores to get a ranking outcome of the audio and/or video data.

Abstract: The present invention discloses new communication device advertising methods for implementing the same. One method discloses by the present invention features downloading the personalized information while making a call; the method comprises the steps of: providing a request signal from the communication device to an information system after a dialing signal is generated on the communication device; generating personalized information, which is the combination of advertising data and value added information, by the information system according to said request signal and advertising data; playing the advertising data on the communication device; after the playing is finished, sending the dialing signal by the communication device to make a call; calculating bonus relating to the call; the user can also decide whether to play the value-added information or not after the call. Another method is pre-downloading the personalized information first and plays it without downloading it while making a call.

Abstract: A contention window adjustment method capable of load-adaptive backoff (LAB) function in a network. At least one middle contention window (CWmid) is set for a station. If the contention window (CW) of a station is greater than CWmid, then that station considers that the network traffic load is heavy. Similarly, if the CW value of a station is no more than CWmid, then that station considers that the network traffic load is light. If collisions occur when the station is transmitting data frames, CW is doubled. Once the station successfully transmits the data frame, CW is decreased by different ratios according to the network traffic load.

Abstract: A contention window adjustment method capable of load-adaptive backoff (LAB) function in a network. At least one middle contention window (CWmid) is set for a station. If the contention window (CW) of a station is greater than CWmid, then that station considers that the network traffic load is heavy. Similarly, if the CW value of a station is no more than CWmid, then that station considers that the network traffic load is light. If collisions occur when the station is transmitting data frames, CW is doubled. Once the station successfully transmits the data frame, CW is decreased by different ratios according to the network traffic load.