Patent Application
20110173638
The present application is based upon and claims priority from prior Japanese Patent Application No. 2010-003291, filed on Jan. 8, 2010, the entire contents of which are incorporated herein by reference.
Embodiments described herein generally relate to an event notifying apparatus and an event notifying method capable of providing event management and notification of related information.
In recent years, information processing apparatus which handle digital data etc. have spread widely. However, such information processing apparatus are insufficient in terms of a reminder function.
For example, JP-A-2005-100300 discloses a technique for providing a shopping site environment with a reminder function of sending an e-mail to a destination specified by a registered member over a computer network as a reminder of an important day that was input by the registered member a certain number of days (specified by the registered member) before that day. This technique also makes it possible, using a reminder, to refer to goods that were sent in the past as well as to order a present.
However, the technique described in JP-A-2005-100300 is such that a user himself or herself registers a date and time of an event. That is, in the conventional technique described in JP-A-2005-100300, it is difficult to automatically extract a future event from photographs taken by the user or mail transmission/reception data.
A general configuration that implements the various features of the present invention will be described with reference to the drawings. The drawings and the associated descriptions are provided to illustrate embodiments of the invention and not to limit the scope of the invention.
According to the embodiments described herein, there is provided an event notifying apparatus including: an extracting module configured to extract a periodically occurring event from acquired input data or a communication history; a predicting module configured to predict a future occurrence time of the event based on a cycle of occurrence of the event extracted by the extracting module; and a notifying module configured to notify an external device about the event based on the future occurrence time predicted by the predicting module.
Embodiments according to the present invention will be described in detail with reference to the accompanying drawings. The scope of the claimed invention should not be limited to the examples illustrated in the drawings and those described in below.
The information processing apparatus 100 includes an HDD 101, a CPU 105, a main memory 106, an AV decoder 112, a non-contact information reading device 113, and an external input/output device 114.
Referring to
The HDD 101 is stored with the OS and the various programs which are necessary for operation of the information processing apparatus 100. In the embodiment, the HDD 101 is stored with an event history management table 104, a preference information management table 103, and a future event management table 102.
The event history management table 104 contains event-related data that were generated by the user and extracted by the event extracting program 107 and event-related data that were generated by the user and extracted by the event extracting program 107 via the non-contact information reading device 113.
The preference information management table 103 contains pieces of user preference information that were extracted by the preference extracting program 109 and data that were extracted by the preference extracting program 109 via the CPU 105 and the non-contact information reading device 113.
The future event management table 102 contains future events for which future event occurrence times were predicted by the event occurrence predicting program 108 based on extracted pieces of event information.
The external input/output device 114 is a device for connection to a network 117 such as the Internet and an external storage device 115 such as an SD card, a USB flash memory, or an external HDD.
The non-contact information reading device 113 receives a getting on/off station name and settlement history information from a cell phone, a credit card, or the like that incorporates a non-contact IC chip.
Each external output device 116 outputs video data or audio data that is output from the AV decoder 112 and event information and related information that are output from the CPU 105.
If a match is found between an event keyword contained in the event history management table 104 or the preference information management table 103 and an event keyword contained in this dictionary, a/the future event management table 102 is generated or updated.
If no match is found, a search is performed using the network 117 to determine future event occurrence times based on event keywords.
An example of an operation of the embodiment will be outlined with reference to
First, at step S210, it is determined whether or not an end instruction has been received from the user. The operation is finished if an end instruction has been received. If no end instruction has been received, it is determined at step S201 whether two hours have elapsed or not. When determined that two hours have elapsed, then it is determined at step S202 whether or not user-generated data has been input newly. When determined that data has been input newly, at step S203 an/the event history management table 104 is generated or updated based on the user-input data. At step S204, a/the preference information management table 103 is generated or updated based on the user-input data. At step S205, a/the future event management table 102 is generated or updated based on the event history management table 104 and the preference information management table 103. At step S206, importance of the event is calculated based on the user-input data and the preference information management table 103 and the future event management table 102 is updated. At step S207, related information is acquired based on the preference information management table 103 and the future event management table 102 is updated accordingly. When determined at step S208 that there exist an event and related information of which the user needs to be notified, at step S209 the user is notified of the future event and the related information.
The details of the operation will be described below.
Upon being powered on, at step S210 the information processing apparatus 100 determines whether or not an end instruction has been received from the user. When determined that no end instruction has been received, then it is determined regularly whether or not new data has been input by the user.
In the embodiment, whether new data has been input or not is determined every two hours. To this end, first, the information processing apparatus 100 determines at step S201 whether two hours have elapsed or not. When determined that two hours have elapsed, then it is determined at step S202 whether or not user-generated data has been input newly. When determined that the user has input new data from the external storage device 115, the network 117, or the like, at step S203 the event extracting program 107 extracts events that are found in the user-input data and generates or updates an/the event history management table 104.
A process for extracting events and generating or updating an event history management table 104 will be described below with reference to
A) The body and the title of a mail are acquired from the network 117 via the external input/output device 114 and subjected to a character analysis, whereby character strings are extracted.
B) A moving image or a photograph taken by the user is acquired from the external storage device 115 via the external input/output device 114 and the content of each event is acquired from metadata or analyzed by an image analysis, whereby character strings are extracted.
C) The contents of a diary written by the user are acquired and subjected to a character analysis, whereby character strings are extracted.
D) An input history of an Internet information sharing service (e.g., blog or profile service) from the network 117 via the external input/output device 114 and subjected to a character analysis, whereby character strings are extracted.
E) A purchase history or a use history of transportation tickets (train tickets) is acquired from the network 117 via the external input/output device 114 and analyzed, whereby character strings are extracted.
F) A goods or ticket purchase history is acquired from the network 117 via the external input/output device 114 and analyzed, whereby character strings are extracted.
G) A getting on/off station history is acquired from a cell phone, a credit card, or the like that incorporates a non-contact IC chip via the non-contact information reading device 113 and analyzed, whereby character strings are extracted.
At step S152, it is determined whether or not a match-found event has been extracted from the event classification dictionary. If a match-found event has been extracted from the event classification dictionary, at step S153 an/the event history management table 104 is generated or updated based on a corresponding event keyword extracted from the event classification dictionary.
If no match-found event has been extracted from the event classification dictionary, an event history management table 104 is not generated or the event history management table 104 is updated and the next user-generated input data is analyzed.
When all input data that have been generated by the user have been analyzed, when determined at step S154 that the generation or update of an/the event history management table 104 succeeded at least once (S154: yes), the process is finished normally.
When all input data that have been generated by the user have been analyzed, when determined at step S154 that the generation or update of an/the event history management table 104 did not succeed even once (S154: no), it means that the generation or update of an/the event history management table 104 has failed and hence the process is finished abnormally. The abnormal ending means that no corresponding event has been found in the event classification dictionary, and usually the process is finished as it is. However, if this state occurs consecutively a prescribed number of times, a certain event may be set.
A specific example will be described below. Assume the following. Occurrence of an event that a mail indicating completion of reservation for hotel A was received on 2008/6/1, occurrence of an event that a mail indicating completion of an order of Father's Day gift from department store A was received on 2008/6/10, and occurrence of an event that a mail indicating completion of payment of a house rent was received from real-estate agent A on 2008/6/20 have become known by analyzing mails. Occurrence of an event that charging was done at station A on 2009/6/25 and occurrence of an event that charging was done at station C on 2009/6/27 have become known from a getting on/off history of the user that is acquired by the non-contact information reading device 113. Occurrence of an event that the user saw a concert held at town A on 2008/6/26 has become known from photograph data that is input from the external storage device 115.
The above events are analyzed and the event classification table (see
Returning to
A process for extracting user preference information and generating or updating a/the preference information management table 103 will be described below with reference to
Preference information is extracted by analyzing the input data by one of the following methods A) to G) etc.:
A) A moving image or a photograph taken by the user is acquired from the external storage device 115 via the external input/output device 114 and colors that appear in preference subject items etc. at high probabilities are found by an image analysis or from metadata, whereby preference information (favorite colors) of the user is extracted.
B) The numbers of times of reproduction by the user of pieces of music and contents are acquired, whereby preference information (favorite pieces of music and contents) of the user is extracted.
C) A history of search words that were input to Internet search pages are acquired from the network 117 via the external input/output device 114 and subjected to a character analysis, whereby preference information of the user is extracted.
D) A goods or ticket Internet purchase history are acquired from the network 117 via the external input/output device 114 and analyzed, whereby preference information of the user is extracted.
E) A getting on/off station history is acquired from a cell phone, a credit card, or the like that incorporates a non-contact IC chip via the non-contact information reading device 113 and the numbers of times of getting-on/off are analyzed, whereby preference information of the user is extracted.
At step S163, it is determined whether preference information has been extracted. When determined that preference information has been extracted, at step S164 a/the preference information management table 103 is generated or updated based on the extracted preference information.
At step S165, event keywords are set using the event classification dictionary (see
For a character string in the preference information management table 103 with which no match is found, “none” is set in the column “event keywords.”
If no preference information is found at step S162, a/the preference information management table 103 is not generated or updated and the next user-generated input data is analyzed.
When all input data that have been generated by the user have been analyzed, when determined that the generation or update of an/the preference information management table 103 succeeded at least once (S166: yes), the process is finished normally.
When all input data that have been generated by the user have been analyzed, when determined that the generation or update of an/the preference information management table 103 did not succeed even once (S166: no), it means that the generation or update of an/the preference information management table 103 has failed and hence the process is finished abnormally.
A specific example will be described below. Assume that an Internet search history is acquired from the network 117 via the external input/output device 114 and analyzed, whereby “firework,” “sale,” “yukata,” and “sushi” are obtained in descending order of the number of appearances among, for example, a prescribed number of latest events for search words. The preference information management table-1 (see
Assume that a getting on/off station history is acquired via the non-contact information reading device 113 and analyzed, whereby “station A,” “station B,” “station C,” and “station D” are obtained in descending order of the use frequency. The preference information management table-2 (see
Assume that user-input photograph data is acquired from the external storage device 115 via the external input/output device 114 and analyzed, whereby “red,” “yellow,” “black,” and “white” are obtained in descending order of the probability of occurrence. The preference information management table-3 (see
Returning to
A process for generating or updating a/the future event management table 102 will be described with reference to
At step S172, it is determined whether or not each event keyword contained in the event history management table 104 and the preference information management tables 103 coincides with an event keyword contained in the event occurrence time classification dictionary. If a match is found, at step S175 a/the future event management table 102 is generated or updated according to the event occurrence cycle and the future event occurrence time that correspond to the match-found event keyword in the event occurrence time classification dictionary. At this time, “not set” is set in the columns “importance” 703 and “related information” 704 of the future event management table 102.
If no match is found between an event keyword contained in the event history management table 104 or the preference information management tables 103 and any event keyword contained the event occurrence time classification dictionary, at step S173 the network 117 or the like is searched for the event keyword via the external input/output device 114.
At step S174, it is determined whether an event occurrence time has been acquired or not by searching the network 117 for an event occurrence time corresponding to the event keyword. If an effective event occurrence time has been acquired, at step S175 the future event management table 102 is updated.
If no effective event occurrence time has been acquired by searching the network 117 for an event occurrence time corresponding to the event keyword, a/the future event management table 102 is not generated or updated.
When the analysis of all of the event history management table 104 and the preference information management tables 103 has completed, if the generation or update of an/the future event management table 102 has completed at least once (step S176), the process is finished normally.
When the analysis of all of the event history management table 104 and the preference information management tables 103 has completed, if the generation or update of an/the future event management table 102 has not completed even once, it means that the generation or update of an/the future event management table 102 has failed and hence the process is finished abnormally.
A specific example will be described below. By searching the event occurrence time classification dictionary (see
Likewise, by searching the event occurrence time classification dictionary, the event occurrence predicting program 108 finds that an event occurrence cycle “once a month” and a future event generation time “around the preceding payment date” correspond to the entry “payment of house rent” in the column “event keywords” 402 of the event history management table 104. A preceding event occurrence date “Jun. 20, 2008” is known from the column “event occurrence date (year/month/day)” 400 of the event history management table 104. Therefore, the future event management table 102 (see
The event occurrence predicting program 108 searches the Internet for event keywords in the event history management table 104 for which no match is found any event keyword in the event occurrence time classification dictionary. In this specific example, no match is found with the event keywords “tour, going out” and “concert” in the event history management table 104. And no match is found with the event keywords “firework, festival” and “sale” in the preference information management table-1 (see
To obtain an effective search result, each event keyword is searched for by taking into consideration the preference information of the user that is contained in the preference information management tables 103. For example, “firework, festival” is searched for also using the station name “station A” which has the first rank in the preference information management table-2 (see
The main purpose of a predicted event occurrence date that is predicted by the event occurrence predicting program 108 is to prevent the event from being forgotten, and hence its precise date need not be presented to the user. For example, the user may be notified of an event earlier than its predicted occurrence time and correct it to an accurate date if necessary. In this example, the user is notified 20 days before an actual event occurrence date. Therefore, the scheduled event notification date of the notification event “Father's Day” is “2009/6/1.”
Returning to
A process for calculating importance levels of events and updating the future event management table 102 will be described below with reference to
First, at step S181, it is determined whether or not importance has been set for every event contained in the future event management table 102.
At step S182, threshold values for calculation of importance is calculated based on user-generated input data. For example, an average is determined for each of such items as the number of photographs, the transportation fee, the amount of payment, and the number of written messages by analyzing event-related data that have been input by the user. Threshold values are set at levels that are higher and lower than the average by 30%, respectively. An event whose value is larger than the plus 30% level is given importance “high,” an event whose value is between the two threshold values is given importance “medium,” and an event whose value is smaller than the minus 30% level is given importance “low.”
If a notification event relates to payment that is indispensable for the living of the user such as payment of any of heating and lighting expenses (e.g., electricity, gas, and heating oil charges), a water charge, or a house rent, at step S183 the notification event is determined an event that is indispensable for living and hence importance “high” is set.
If the notification event is determined not indispensable for living and if effective input data generated by the user exists for the notification event and comparison with the threshold values is possible (S184: yes), at step S185 importance is determined through comparison with the threshold values.
Among the events contained in the future event management table 102, importance “medium” is given to events for which comparison with the threshold values cannot be made because of absence of effective input data generated by the user, events relating to the national holidays that are set by the National Holidays Law, events relating to yearly events that relate to historical events, and events each of which does not belong to any category. Examples of such events are Father's Day, Children's Day, Respect-for-the-Aged Day, and Christmas Day.
A specific example will be described below. Since the event “Father's Day” contained in the column “notification event” 1002 of the future event management table 102 (see
Finally, since the event “information of sale of tickets for viewing of firework display to be held at town A” does not belong to any category, it is given importance “medium” and the column “importance” 1003 of the future event management table 102 (see
Returning to
The related information acquiring program 111 searches the Internet using, as a search word, a notification event (1002) contained in the future event management table-2 (see
The related information acquiring program 111 searches the Internet using, as search words, a combination of a notification event (1002) contained in the future event management table-2 (see
A specific example will be described below. For example, a search result of the notification event “information of sale of tickets for viewing of firework display to be held in town A” and a search result of a combination of the notification events “information of sale of tickets for viewing of firework display to be held in town A” and “red” are entered into the column “related information” 1004 as shown in the future event management table-3 (see
Returning to
As for the manner of notification of related information, it is possible to notify the user of only an event first and to display related information later (see
A specific example will be described below. An external output device 116 is notified of an event with power-on timing on a day contained in the column scheduled event notification date (year/month/day)” 1100 of the future event management table-3 (see
When the importance (1103) of a notification event (1102) contained in the future event management table-3 (see
In this example, when the importance is “high,” the notification interval is set at one day and two or more external output devices 116 are informed of the re-notification event (see
Only importance is employed in the embodiment, urgency may also be taken into account.
The method of extracting an event history via the external input/output device 114 that is described in the embodiment does not restrict the event history extracting method. For example, an event history may be set freely by a user operation.
The operation starting method of the embodiment in which whether or not new data has been input by the user is checked every two hours does not restrict the operation of the apparatus. Operation may be started with timing that new data is input from by user or an instruction is received from the user.
The future event occurrence predicting method of the invention does not restrict the future event occurrence predicting method. For example, a future occurring event may be set freely by a user operation.
The method of extracting preference information of the user via the external input/output device 114 that is described in the embodiment does not restrict the preference information extracting method. For example, preference information may be set freely by a user operation or a preference may be predicted based on a profile that is registered by the user in advance.
The content, the notification timing, and the notifying module of a message for notifying the user of an event that is described in the embodiment does not restrict the event notifying method. A message may be presented by other methods such as voice output.
The algorithm for determining importance of an event that is described in the embodiment does not restrict the method for calculating a predicted future event occurrence time. For example, importance may be determined freely by a user operation.
The timing and the means for notifying the user of related information which are described in the embodiment do not restrict the related information notifying method. The user may be notified of related information simultaneously with an event or by other methods such as voice output.
The method of extracting an event history via the external input/output device 114 which is described in the embodiment does not restrict the event history extracting method. An event history may be set freely by a user operation.
As described above, in the embodiment, a future occurring event is extracted automatically from photographs taken by the user or mail transmission/reception data. The user need not register a date and time of an event.
The embodiment provides an advantage that the means for automatically extracting a future occurring event from photographs taken by the user or a mail transmission/reception data, determining its importance, and performing its notification makes it possible to eliminate complicated work the user has been required to do to manage events by himself or herself.
Furthermore, presenting the user with information that relates to a future event occurrence time allows the user to encounter various goods or new events.
By automatically extracting a future occurring event, determining its importance, and performing its notification, the user is allowed to be freed from complicated work for managing events by himself or herself.
According to a component for also presenting the user with related information that relates to an event and conforms to preference information of the user in notifying the user of the event allows the user to encounter new goods or events that the user has not been aware of. This provides an enhanced advertisement effect because the user would be interested in the event around the time of its occurrence.
(1) The event extracting program 107 takes in user-generated input data or a communication history, extracts a periodically occurring event from the thus-taken-in input data or communication history, and generates or updates an event history management table 104.
(2) The preference information extracting program 109 extracts preference information of the user from user-generated input data or a communication history and generates or updates a preference information management table 103.
(3) The event occurrence predicting program 108 predicts a future event occurrence time based on event occurrence time information that is acquired by searching the network 117 via the external input/output device 114, an event history, preference information, etc., and generates or updates a future event management table 102.
(4) The event importance calculating program 110 calculates importance of an event based on user-generated input data, a communication history, and preference information, and updates the future event management table 102.
(5) The related information acquiring program 111 acquires related information that relates to a future event and conforms to preference information of the user by searching the network 117 via the external input/output device 114, and updates the future event management table 102.
(6) The event occurrence predicting program 108 notifies an external output device 116 of future occurrence of an event together with related information by a method that is suitable for its importance.
Although the embodiments according to the present invention have been described above, the present invention is not limited to the above-mentioned embodiments but can be variously modified. Constituent components disclosed in the aforementioned embodiments may be combined suitably to form various modifications. For example, some of all constituent components disclosed in the embodiments may be removed or may be appropriately combined.
Additional advantages and modifications will readily occur to those skilled in the art. Therefore, the invention in its broader aspects is not limited to the specific details and representative embodiments shown and described herein. Accordingly, various modifications may be made without departing from the spirit or scope of the general inventive concept as defined by the appended claims and their equivalents.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2010-003291 | Jan 2010 | JP | national |
