KR20160104067A - Generating a news timeline and recommended news editions - Google Patents

Abstract

The described embodiments enable presenting to the user news articles or other content that are likely to be of interest to the user and that are temporally and / or geographically related to the user's location or area of interest. The news delivery system includes an ingest module that assigns topics, locations and dates to available content, a profile engine that determines profile topics and geographic locations that a particular user is interested in, and an operation of the ingest module and profile engine And a news delivery module for selecting content for the user based on the desired time frame. In one embodiment, the profile engine performs attenuation processing to remove old topics and locations from the user's profile. In related aspects, the profile engine maintains multiple profiles for the user.

Description

{NEW GENERATING NEWS TIMELINE AND RECOMMENDED NEWS EDITIONS}

The described embodiments relate to the display of news articles for users of computing devices, and more particularly to the selection and display of news articles related to a user's geographic interest or specific topics over time.

Users of computers, tablets, smart phones and other network-enabled devices can access news content via the network. For example, many newspapers and periodicals have online editions available to readers at no charge or through various subscription policies.

Many news consumers access this content directly, for example by accessing the URL to the website associated with the news source itself, but other consumers are essentially presenting the news content from other sources to the user in a single user interface Uses news aggregators. The news consumer may then select specific content of interest and be directed to that content via the news aggregator.

Many topics disappear from the headlines and reappear after a few weeks, months, or years. Some news consumers may not be familiar with the historical context of a particular topic, and this results in a reduction in the ability to recognize potentially negative user experiences, such as the significance of the current story.

The described embodiments make it possible to present to the user news articles or other content relating to a particular topic or location that has been created or published in the time frame of interest of the user or geographically related to the user's location or area of interest .

The news delivery system includes an ingest module that assigns topics and locations to available content, a profile engine that determines news sources and geographic locations, a profile engine that determines which users are related, and an operation of the ingest module and profile engine And a news delivering module for selecting content for the user based on the received content.

In one embodiment, the profile engine performs decay processing to remove old topics and locations from the user's profile. In related aspects, the profile engine maintains multiple profiles for the user,

1 is an illustration of a system for providing news content to users according to one embodiment.
2 is a flow chart illustrating high level steps for providing news content that is topicually and geographically relevant to a user.
FIG. 3 illustrates a method for determining a user's reading interests according to one embodiment.
4 shows a profile engine according to one embodiment.
5 is a flow chart illustrating a method for displaying news content geographically and topic related to a user according to one embodiment.
Figure 6 illustrates a user interface for displaying a geographic area of interest according to one embodiment.
Figure 7 illustrates a user interface for displaying news content in association with a map according to one embodiment.
Figure 8 illustrates a user interface for displaying news content in association with a map according to one embodiment.
9 illustrates a user interface for displaying news content in association with a map according to one embodiment.
10 illustrates an example of a user interface for specifying a topic of interest and a time frame according to one embodiment.
11 is a flow chart illustrating a method for displaying news content geographically, temporally, and topic related to a user according to one embodiment.
12 illustrates an exemplary computer architecture in accordance with one embodiment.
The drawings illustrate embodiments for illustrative purposes only. It will be readily apparent to those of ordinary skill in the art, from the following discussion, that alternative embodiments of the structures and methods illustrated herein may be utilized without departing from the principles set forth herein.

System outline

FIG. 1 illustrates a system 100 for providing geographically and temporally relevant news to a user according to one embodiment. The system 100 includes an ingest module 102, a profile engine 112, and a news delivery module 114. The ingest module 102 further includes a topic analyzer 104, a geococator 106, an indexer 118, and an article database 108. The profile engine 112 includes a user recommendation generator 116 and a user profile database 110. The news delivery module 114 includes a map engine 122 and a timeline engine 124. A plurality of news sources 120a, 120b, 120c (generally 120) and a user device 130 are also shown in FIG. Each of these is described in further detail below. It is noted that although some or each of each of these elements is shown in FIG. 1, it should be understood that when implemented, the system 100 may include several corresponding logical or physical modules that perform the features described herein do. Although only one user device 130 and three news sources 120 are shown for ease of illustration, hundreds, thousands or even such devices can be used with the system 100. [

The system 100 communicates with news sources 120 and user devices 130 via a network (not shown). The network is typically the Internet, but may be any network, including but not limited to any combination of LAN, MAN, WAN, mobile, wired or wireless networks, private networks, or virtual private networks. The system 100 is connected to the network via a network interface.

The news source 120 includes text, audio, or video content, or a combination thereof, that is accessible to the system 100 and directly or indirectly to the user device 130 over a network, such as the Internet. Each news source 120 provides one or more news content items in an ad hoc or periodic manner. For example, the news source may be a website related to a magazine, newspaper, radio station or television station. The news source 120 makes its content available to viewers, such as the system 100 and the user device 130, for free or at a cost. In this description, we refer to this type of content as interchangeably referred to as news content, news articles, and articles. However, one of ordinary skill in the art will appreciate from the present disclosure that the described embodiments, by themselves, have applications for any corpus of documents with topics and locations generally associated with news content as well I will understand.

The ingest module 102 discovers, analyzes, and indexes the news content provided by the news sources 120. The indexer 118 crawls and discovers news articles 120 and any articles available through their sources in one embodiment. Topic analyzer 104 and geococator 106 make weighted topics and locations as indexed news content and store an indication of content and attributes in article database 108 as described in detail below.

The profile engine 112 processes the user-specific information, as described in detail below with respect to FIG. 3, to obtain and store user characteristics related to which content may be appropriate for the user. Recommendation generator 116 provides a process for determining which data that is made available by news source 120 is most appropriate to be presented to user device 130, as described in detail below. The user recommendation generator 116 generates specific content for the user device 130 based on the results of queries to the indexer 118 and profile information available to the user.

The news transfer module 114 provides the user device 130 with a curated list of news articles relating to the topic or set of related topics. In one embodiment, the news transfer module 114 presents a web site or mobile application that contains a list of news content items that can be classified according to a user interface, e.g., their related topics or location. The user of the user device 130 may select the items of interest and then be directed to the selected items. For example, a user may select a thumbnail image or snippet of an article and be directed to the website hosting the content, i.e., the news source 120. In various embodiments, the news transfer module 114 recommends content items related to specific locations of interest, topics of interest, time frames of interest, or combinations thereof, as described below.

User device 130 may be a laptop or desktop computer, a smartphone, a tablet, or any other device capable of accessing system 100 and news source 120 via a cellular or wide area network. The user operating the user device 130 may be an individual, a group of individuals, a corporation, or an automated computer system. For ease of description, we will generally refer to as "user ", and the ordinary skilled artisan will recognize that it includes the user himself, the user's device, or a combination of the two, as may be appropriate in the context will be.

Process outline

2 is a flow chart illustrating high level steps for providing news content that is topicically, temporally, and geographically relevant to a user. System 100 obtains news content from news sources 120 and annotates 202 according to topics and locations related to the content. The profile engine 112 determines (204) the topics and locations that are part of the user's read interests and maintains the information in the user profile. The recommendation generator 116 selects (206) the content from within the desired time frame matching the user's interest and recommends the content to the user (208). We describe each of these steps in more detail below.

Indexing and topic / location properties

As the indexer 118 discovers a news content item, the topic analyzer 104 identifies one or more topics to be associated with the content item. In one embodiment, the topics are identified using a Google Knowledge Graph database of topics (not shown). This database contains a very large collection of known topics, as well as connections between topics based on their relevance to each other. In other embodiments, different sets of topics may be used as appropriate for the operating environment.

In one embodiment, the ingest module 102 is configured to receive any new item of content (e.g., a news article) provided by the news source 120 and annotate the item with topics. For example, if the word "United" appears multiple times in relation to terms on air travel in a new entry, the topic "United Airlines" or "UAL" will be commented on that entry. Instead, if the word "United" appears multiple times in connection with terms associated with transport or moving companies, the topic of "United Van Lines" will be annotated on that item. In some embodiments, a weight is associated with each such annotation. For example, it may be very clear that United Airlines is intended more than United Van Lines for an item, but in others it may be somewhat unclear which company topic corresponds to the item. In some embodiments, the ingest module 102 processes millions of new items each day and is implemented using portions of the Google Knowledge Graph functionality mentioned above.

In these embodiments, the topic analyzer 104 uses the two steps to find the most relevant topics for the item. The first step involves looking for all the topics actually mentioned in the entry. For example, the word "United" is exactly the same as at least two known topics based on the discussion above, so that they are considered candidates, and other terms in the entry (e.g., "passengers" and O'Hare ), The knowledge graph function selects one and weights it based on, for example, how often the topic appears in the item. The second step finds related topics that are not explicitly mentioned in the item and also recovers the topics based on their relationship to other topics. For example, if a news article discusses problems facing major airlines, but does not mention one of those airlines, the topic corresponding to that missing airline may nevertheless be added. Similar processing can be used for rescaling - if only the topics identified in relation to the news article are very closely related topics, then the weight of each of these topics can be increased. In other embodiments, different weighting schemes are used as appropriate for a particular application.

The topic analyzer 104 annotates the news items with the next weighted topics, and stores an indication of the news content, its serving or distribution date, and its associated weighted topics in the article data 108.

The geococator 106 also processes news items to identify any geographic references contained within the content item itself, or any associated metadata. For example, the content item could be a news article such as United Airlines from the above example, and the article could discuss the big presence of United in Chicago. Or articles can explain recent weather events in Boston, Massachusetts; Name to live in the United States; Or news features relating to the best cities mentioned several times by an item including a date line that identifies where the news story was submitted. The geococator 106 identifies geographic locations such as those described above in a manner similar to how the topic analyzer 104 discovers topics related to news content items. The geococator 106 annotates the content item to a geographic location and stores geotagging information along with the content and topic display in the article data 108. Based on the annotated content, the indexer 118 therefore includes topics related to the particular news content item; Geographical points associated with a particular news content item; News articles related to specific topics; And news articles related to specific geographic locations. Also, since each content item has an associated serving or distribution date, the indexer 118 may determine that the content item is within the time frame specified in the request (or within the default time frame, if the time frame is not otherwise specified in the request, , Past day, week, month, year, etc.).

Determining users' read interests

Referring now to FIG. 3, an embodiment of a method 300 for determining news content interests of a particular user is illustrated. It should be noted that similar techniques may be applied to determine news content interests of certain groups of users and may also be applied to individuals in the group and then to individuals having similar characteristics to those in the group . In the example shown in FIG. 3, the process begins at step 310 by obtaining a profile corresponding to the user from the user profile database 110. The profile may include user-identified interests, and, if the user has such rights, historical information about articles read by the user, news sources preferred by the user, and geographic areas of interest to the user. Such as automatically stored information related to the interests of the user. In one embodiment, when the user opens a mobile application or a web service (such as Google Play Newsstand), the method 300 includes retrieving related profile information (e.g., a user ID, an ID of an open article, Time and a scored list of user interests for subsequent processing). For offline access, information about which articles have been opened and the time of access is stored and sent to the user profile engine 112 at the next time the user comes online.

At step 320, the user profile engine 112 fetches the article information from the article database 108 as described in detail above and obtains the scored topics and locations generated for that article. Next, in step 330, the user's interest information is fetched. This can be done from the profile information previously obtained in step 310, or just a new request for this aspect of the profile information can be made according to the usage environment and which technique is most effective. The interest information from the profile may be blank (e.g., for a new user) or may include both user statistics (last update time / counter information) and a set of scored topics and locations. Each scored topic includes a topic ID, a score for the topic for this particular user, and time / counter information for this topic for this user. Similarly, each scored location includes a location indication, a score for a particular location for this user, and time / counter information for this location for this user in various embodiments.

The topics and locations from the article are then added to the profile of the user (at step 340) (as a score for each topic and each location) as follows. If the user's profile already contains a topic, the score for that topic is increased using a predefined mathematical function. In one embodiment, the user's score for a particular topic is incremented by an appropriate amount each time the user reads the article corresponding to the topic. The score for the location in the user's profile is similarly increased. Continuing the example of O'Hare mentioned above, the user's O'Hare score can now be 10 and the Chicago score can be 3; When a user reads an article with an O'Hare topic score of 0.5 and a Chicago location score of 1, the user's new score for O'Hare is increased to 10.5, and the user's new score for Chicago is increased to 4. If the profile does not already contain a topic or location, a new scored topic or scored location is added to the profile in a similar manner. In this step, the last update time for each topic and location is set to the current time, the counters for the topic and location are incremented; The last update time for the profile is also updated, and the counter for the profile is also incremented. In some embodiments, if the last update was the most recent one or more of the counters were not incremented, so that all updates occurring within a predetermined time period (e.g., days) are treated as one.

Periodically, the scores of the topics and positions in the profile are attenuated (350) using a predefined damping function; In one embodiment, the exponential decay is used to appropriately abort the user's previous interests step by step and rank the newer interests higher. By comparing the last update counter of the topic or location with the last update counter of the profile, it is known how many times the user has read content that is not related to the current topic or location. Therefore, "old" topics and locations are demoted over time. Although step 350 is illustrated in this embodiment as being performed in conjunction with profile updating, in other embodiments, attenuation processing may be performed, for example, when processing resources become more available (e.g., Lt; RTI ID = 0.0 > periodically < / RTI > during a day's time) independent of any particular update at a time. At step 360, the low scoring topics and locations are truncated, i.e. removed, from the user's profile. This helps to reduce processing overhead. However, it should be noted that the attenuation rate for the topic and the attenuation rate for the position may be significantly different to reflect the topics or locations that are considered to be more important, or to reflect observations about user behavior that occur during implementation do. In some embodiments, damping processing is not performed. Processing for this method is then completed (370).

In some embodiments, multiple profiles are generated for the user to improve the performance of system 100. For example, monthly profiles are created in one embodiment to provide a view of the topics and locations that the user is most interested in at a particular time of the year. Although water skiing and colder destinations may fall off the user's profile in the fall, they can become important again next month, and using these multiple profiles for a particular user, cycling interests can be captured. Likewise, separate profiles for the various categories can be maintained for each user to better understand the topics of interest to the user. For example, a separate profile for the user regarding presidential elections that would otherwise be damping processing 350 would be maintained over a period of years. The scored topics thus generated for each profile are then used to generate recommendations and score the search results, as described elsewhere herein.

The user profile data storage 110 includes information about individual users to facilitate operation of the system 100. The scored information includes identification information about the user. In some embodiments this is information manually provided by the user, but in other embodiments the user may request that this information be obtained automatically, for example, from other entities that the user has subscribed to or other subscriptions the user has . The profile data 110 maintains scored or weighted lists of topics that the user is most interested in, such as those detailed below.

Recommendation of content for users based on their interests and location

4 shows a functional view of the recommendation generator 118 used as part of the profile engine 112. As shown in FIG. The recommendation generator 118 is used by the profile engine 112 to take information about a particular user and to determine from that information which content to present to the user via the news delivering module 114.

Recommendation generator 118 includes various subsystems to facilitate its operation. 4, Recommendation generator 118 includes a profile filter 402, a selector module 404, a mixer 406, and a de-duplicator 408. Many of these subsystems interact with each other, as described below.

The profile fetcher 402 provides a mechanism for identifying topics, locations, and news sources for which an individual user appears to be interested. In one embodiment, these topics and locations are stored in the user profile database 110. In some instances, such topics may be manually identified by the user, but in other instances they are automatically generated based on observation of user behavior. In some embodiments, the user ' s current position is used as an input to the recommendation generator 118. [ The location of the user may be explicitly reported by the user or the user's device, or may be derived from the user's IP address or other geocaching methods known in the art. The operation of the profile fetcher 402 provides the provision of a list of topics and locations with scores that represent the things that the user is most interested in.

Recommendations generator 118 obtains corresponding content (e.g., an indication of articles or other items) stored in article database 108 when topics and locations are acquired. In one embodiment, for example, this is accomplished through a request to the indexer 118 of the ingest module 102. In various embodiments, in order to reduce the number of returned articles that are not of interest to the user, the ingest module 102 is indexed by the geo-locator 106 as located within the maximum distance of any location specified in the request It returns only that content. For example, a request to indexer 118 may include "travel", "airlines", and "United Airlines" as topics and "Boston", "San Francisco", and "Auckland" as locations. The indexer 118 will then return the content items matched to those topics and located within the maximum distance of any of the listed locations. In various embodiments, the maximum distance may be specified in the request, or it may be configured by the user or the enforcer.

Depending on the specified topics and locations, the body of content obtained from the indexer 118 may be considerably larger than desirable to present to the user. In various embodiments, the selector module 404 scales the content according to a function appropriate to the attribute of use. In one embodiment, a predefined scoring function is used that includes such factors as location, topic relevance, content quality, edition quality, popularity, and freshness. Location may be automatically provided to the system 100 by the device 130 (determined based on the IP address or other geo-casting technique by the system 100 as described above) Items geographically tagged by the geo-locator 106 to locations that are geographically closer to the location of the user device 130 (which may be explicitly provided by the geo-locator 106) receive a higher score. For relevance, items with more topics overlapping the user's profile receive a higher score. For content quality, images with higher resolutions (or resolutions that are more appropriate for the user's bandwidth) are scored higher; Audio with more appropriate characteristics for the user (e.g., a higher sampling rate for one user and a lower file size for another user) is scored higher; The text having the most appropriate word counts and read levels for the reader is scored higher (e.g., based on self-identified or automatically determined historical preferences). For the edition quality, the content from the editions previously determined to be "good" is scored up above others. For popularity, the content read by more users (in some embodiments, more users with characteristics similar to those of the current user, in particular) is scored higher than other content. For freshness, more recently posted content gets a higher score. When all of the items are scored, they are sorted according to their score.

In some embodiments, other algorithms are also used to pull content in from other sources. For example, a separate algorithm may be employed to obtain additional items from sources that the user frequently reads / views / listens to, or to obtain articles on topics or locations where the user has most recently shown interest Lt; / RTI > One of ordinary skill in the art will appreciate that for large amounts of content, server class computers may be used to simultaneously make multiple requests for content, and other known techniques may be used to ensure that the processing described herein is completed quickly and efficiently Lt; / RTI >

The mixer 406 then combines the results from the operation of the selector module 404 to produce a personalized edition of various items to be presented to the user via the news delivery module 114. In one embodiment, the mixer 406 is explicitly limited to include a fixed number of sets of items, each of which is derived from the items obtained by the selector module 404. For example, one personalized edition may be configured to include two articles from the user's location, two articles from sources that the user frequently reads, and two articles from topics that the user most often reads. In other embodiments, only the mixer 406 articles in the user location (s) of interest are included.

In some instances, the operation of the mixer as described above may generate articles for one set that is substantially similar to the other set of articles. Therefore, the dispatcher module 408 analyzes the selected items to determine if they are quite similar. In one embodiment, the deduplicator module 408 compares the topics in each article identified as candidates for the set with all other articles already selected by generating a similarity score. One of ordinary skill in the art will recognize that machine learning algorithms such as cosine similarity may be readily applied to generate such similarity scores. Depending on the variety of information desired, a threshold of similarity score is applied to reject a proposed new article based on this similarity.

In another embodiment, the despatcher module 408 is not applied until all the sets are populated. In this example, if too much similarity is detected than one of the items contributing to the over-threshold similarity score is rejected, the mixer 406 selects a replacement item, and the duplicator module 408 selects It is repeatedly operated until such time that the threshold value is not exceeded.

As noted, some environments may contain millions of items of content, and system 100 may be operated for millions of users, so the scalability of the process may be significant in these circumstances. If this is a problem, well known scaling techniques such as pre-computation and storage of results are applied to speed up processing and minimize processor and memory requirements.

Recommendation of content for users based on topics and time frame

In some embodiments, when a user is interested in exploring a particular topic or set of related topics over a range of times (i.e., a time frame), the recommendation generator 116 may generate a news Articles are structured to recommend.

As described above, the profile engine 112 utilizes the recommendation generator 118 to determine what content to present to the user via the news delivery module 114. In various embodiments, the request to the indexer 118 of the ingest module 102 includes topics of interest to the user as well as the time frame of interest, and may also include any locations of interest. Returning to the example described above, the user may be interested in learning about the history of United Airlines for the past 50 years, and requests to indexer 118 may include topics such as "travel", "airlines", and "United Airlines &Quot;, and a date range specifying the previous 50 years. This request can also be made to "Boston", "San Francisco", and "San Francisco" to further limit the results, for example if the user is particularly interested in the history of United Airline over the previous 50 years, Auckland "as locations.

In various embodiments, the selector module 404 utilizes a scoring function that takes into account the popularity of each news item as described above and in relation to its serving or distribution date. For example, selector module 404 may receive several articles from 1988 that describe an event that occurred that year (e.g., the fastest flight in the world) from indexer 118. The selector module 404 determines which one (or how many, depending on the preference of the enforcer), depending on the popularity of each article to select as representing the event. The selector module 404 may determine, for example, that the most popular article-that is, the article with the highest read count-is scored as the highest, so that it is selected to represent the event in the timeline. The selector module 404 also applies the above described criteria in various embodiments in determining the score for each article.

In one embodiment, the selector module 404 also increases the score for articles posted by the news source 120 identified by the profile engine 112 as being normally of interest to the user. This increases the likelihood that the timeline of the stories presented to the user will include stories across the timeline from the set of sources the user enjoys. Providing users with articles posted by the same sources over a period of time can also improve the user experience and allow the user to view the evolution of the story from a particular perspective (such as from a particular newspaper or periodical) .

The mixer 406 combines the results from the operation of the selector module 404 as described above to produce a set of items to be presented to the user and the duplicator module 408 provides the described deduplication functionality do.

Delivery of geographically and topic related news to users

In one embodiment, the news transfer module 114 includes a map engine 122 that enables a user to utilize the map interface to identify and consume news content based on location attributes of the content. We describe the functionality of this feature below in conjunction with FIG. 5 in the combination of FIGS. 6-9.

In one embodiment, the user accessing news map engine 122 may indicate that it wants to view news items through a map based selection. This may be selectable via a user interface element, such as a button or link on a news reading page, presented as an option within, for example, a news reading application. In one embodiment, in response to user operation of this feature, and referring to Fig. 6, a map 600 is presented to the user device 130. [ A user interface (not shown) may be used by the user to specify 502 (FIG. 5) the area of interest for display. In one embodiment, the map is centered at the current location of the user device if known. Alternatively, the map may be centered on or included in a location known to be the user's interest, based on the user's profile, as described above. Map engine 122 then displays a map associated with the user interface (504). In the example of FIG. 6, the map 600 includes the city of Boston.

Map engine 122 then identifies relevant stories to be displayed to the user. In one embodiment, the map engine 122 passes the location of interest to the recommendation engine 116, which fetches (506) the articles located in the displayed area and generates a map engine 122 Sends a search request to the indexer 118 for articles previously identified by the geocataloger 106 as being relevant for the location displayed by the geocoder 106. [ In one embodiment, the map engine 122 provides latitude and longitude coordinates to the recommendation engine 116, but any other suitable method for locating the location may be used.

The recommendation engine 116 receives and scans 508 the articles related to the topics and locations of interest as described above, and provides the maps engine 122 with a representation of the matched articles and their locations. The scored articles represent the best articles to recommend to that particular user within that geographic area.

The map engine 122 then displays 510 information about at least some of the top scoring articles to the user. FIG. 7 shows an example of a user interface displayed with an indication of articles associated with the map 700. FIG. In the example of FIG. 7, an indication of the articles (in the illustrated case, photos, headlines, and news sources) 702 is displayed along one side of the user interface. A series of markers 704, 706, 708, 710, 712 are placed on the map 700 to display a particular location associated with each of the displayed articles 702. In one embodiment, the map engine 122 utilizes geolocation information associated with each article and renders the marker at a precise or approximate location on the map 700. In various embodiments and depending on the specificity of the geographic information, map scale, etc., the exact placement of the markers on the map 700 may indicate an exact or approximate location for each article. In some map resolutions, for example, when a map is scaled out to represent an entire week, province or country, different markers may be rendered to indicate that clusters of news articles share a marked location.

8, in one embodiment, when a user provides an input to identify a particular marker 802 on a map 800, the map engine 122 displays a particular article 804 associated with the marked location The display is updated. For example, depending on the hardware characteristics of the user device 130, a user may mouse over the markers 802, tapping the markers 802, or providing inputs to identify the markers. In response, in one embodiment, the map engine 122 removes news items 702 that are not related to the displayed location, leaving only the associated article (s) 804. The map engine 122 may scroll the display to remove the unmarked articles or simply remove them from the displayed user interface. In the example of FIG. 8, the unmarked articles were scrolled vertically from the top and bottom of the screen, and portions 806 and 808 of some of the unselected articles showing as a visual cue to the user that other articles were present Leave it.

In an alternative embodiment, rather than selecting the marker 802 and causing the associated article 804 to be displayed, the user may select one of the displayed articles 702, and the map engine 122 may select one of the displayed stories 702, And updates the displayed map 800 to highlight the marker 802 associated with the location. Markers highlight markers, enlarge their size relative to other markers (as shown in FIG. 8), or flash a marker, change its color, provide another visual cue, And can be emphasized in a number of ways such as by any combination.

9, when the user selects another marker 902 or other story 904, the map engine 122 displays the selected story 904 and highlights the marker 902 having the associated location And updates the map 900 displayed for the user.

In response to the user selecting one of the displayed articles 904, the device 130 displays the actual article. For example, in one embodiment, by double-tapping or double-clicking on the text in the article display 904, the user device 130 launches a web browser window and, at a location specified by the news delivery module 114, Is displayed. The location may be specified, for example, by a link provided with an article display on the user device 130, or the user device 130 may send a request for that location in response to the user selecting an article display, ). At any event, the user can then be directed to the article and read, hear, or view the requested information.

Still referring to FIG. 5, if the user implicitly or explicitly provides new coordinates, such as by scrolling the map or writing a new location in the search field, the map engine 122 takes the new coordinates (512) , Re-centers the map displayed at the new coordinates (514), and displays the updated map (504). The map engine 122 then acquires articles relating to the new location, scales them according to the user's interests, and displays an indication of the top scoring articles on the new map in the process as described above.

Communicate topic-related and temporally related news to users

In various embodiments, the news transfer module 114 includes a timeline engine 124 that allows a user to specify, via a user interface, a time frame in which the user desires to view the news content. As described below, the timeline engine 124 functions as a separate feature in one embodiment, or as a map engine 122 in conjunction with other embodiments.

In one embodiment, and now referring to FIG. 10, the user interface 1000 illustrates a manner in which a user may specify a time frame of a topic of interest and a reference in accordance with one embodiment. The interface 1000 includes a text box 1002 in which a user can specify a topic to be searched. Control elements 1004 allow the user to specify a time frame of interest. In the illustrated example, the user may choose from this year, the last 5 years, the last 10 years, or provide the designated dates. In one embodiment, the interface 1000 includes a visual timeline (e.g., a timeline) to preview the results based on the input provided in the text box 1002, and a user to edit the timeline displayed using the interface control elements Line 1006. < / RTI > As will be appreciated by those of ordinary skill in the art, many other user interface controls may be provided to enable selection of a time frame by the user.

In various embodiments, in addition to providing a relevant time frame for a topic, a user may also specify an associated geographic area, as described above.

Figure 11 illustrates a method for providing articles of interest to a user based on location and within a specified time frame. For example, with reference to FIGS. 10 and 6, the user interface as described above may be used to specify 1102 the region of interest and the time frame of interest to the user. In one embodiment, the map engine 122 displays a map associated with the specified location (1104). The map engine 122 and the timeline engine 124 identify relevant stories to be displayed to the user. The recommendation engine 116 is located in the relevant geographic area and fetches the published articles within a specified time frame 1106 and sends the search request for the relevant articles to the map engine 122 And the time frame provided by the timeline engine 124. The time-

The recommendation engine 116 receives and scans 1108 relevant articles for the topics of interest, location and time frame as described above, and stores the articles matched to the map engine 122 and timeline engine 124 Display, locations and times. Scored articles represent the best articles to recommend for that particular user regarding a particular topic selected from a specified time frame and associated with a specified geographic area.

The map engine 122 and the timeline engine 124 then display 1110 information regarding at least some of the highest scoring articles to the user. In one embodiment, geographic matches are displayed on maps using markers such as those described above with respect to Figures 6-9. In addition, in various embodiments, the timeline engine 124 displays a visual timeline that places markers at points along the timeline that correspond to each of the recommended stories. In one embodiment, as the user displays, for example, by marking on a marker on the timeline, the display of the associated story, for example, makes the thumbnail associated with the story larger, Removing information, and the like. Similarly, in response to the user displaying an indication of a particular story, the corresponding marker on the timeline can be highlighted to indicate its relevance. These temporal associations with stories may be such that the geographic constraints, in conjunction with temporal constraints by the user, are not necessarily the same as the geographical relevance (as described above with respect to Figures 7 to 9) Lt; / RTI > interface.

In various embodiments, the user may adjust the timeline contained within the user interface, e.g., having the appearance of a timeline 1006 (FIG. 10), or may display a modified time frame of interest 1112). In response, the timeline engine 124 coordinates (1114) the displayed timeline and sends a request to the user via the recommendation generator 116, such as described above, indicating the changed timelines and the new timeline to the appropriate markers Update.

In situations in which the systems or components discussed herein collect personal information about users or may use personal information, users may be able to access information about the user (e.g., the user's social network, social Information about actions or activities, occupation, user preferences, or the user's current location), or whether to receive content from a content server that may be more relevant to the user and / or how to receive You may have an opportunity to control your legs. In addition, the personally identifiable information is removed since certain data may be processed in one or more ways before it is stored or used. For example, the identity of the user may be processed such that personally identifiable information may be determined for the user, or the user ' s geographic location may be generalized when location information is obtained (city, ZIP code, , Etc.), the user's specific location can not be determined. Thus, the user can control how information is collected about the user and used by the content server.

The system 100 is implemented in some embodiments by a network of server class computers that includes one or more high performance CPUs and one or more gigabytes of main memory, as well as storage in the range of hundreds of gigabytes to petabytes. Operating systems such as LINUX are typically used. The operations of the system 100 and its component components may be performed in hardware (e.g., dedicated computing devices or daughter boards within general purpose computers), or in computer storage on the servers of the system 100, May be controlled via computer programs executed by the processors of these servers to perform the functions described in connection with FIG. More details regarding the implementation of these machines are provided in connection with FIG. Those of ordinary skill in the art of system engineering and, for example, hosting media content or delivering content, will readily determine the configuration and operation of such computer programs and hardware systems from the functional and algorithmic descriptions herein.

The article database 108 and the profile database 110 may be stored in a computer readable storage medium such as a hard disk drive, a RAM, a writable compact disk (CD) or DVD, a solid state memory device, or other optical / magnetic storage media, Lt; RTI ID = 0.0 > a < / RTI > As other types of computer-readable storage media can be used and new storage media are developed in the future, they are expected to be able to be configured in accordance with the above described descriptions.

In this description, the term "module" refers to the calculation logic for providing a specified function. The module may be implemented in hardware, firmware, and / or software. Where the modules described herein are implemented as software, the modules may be implemented as standalone programs, but may also be implemented as part of a larger program, as a plurality of separate programs, or as one or more statically or dynamically Lt; / RTI > may be implemented via other means as libraries linked with < RTI ID = 0.0 > It will be appreciated that what is referred to herein as a module represents one embodiment of the invention, and that other embodiments may include other modules. Further, other embodiments may not have the modules described herein and / or may distribute the functions described between the modules in a different manner. Additionally, the functionality contributed to more than one module can be integrated into a single module. In embodiments where modules are implemented by software, they may be stored on a computer-readable persistent storage device (e.g., a hard disk), loaded into memory, and executed by one or more processors included as part of the system 100 . Alternatively, hardware or software modules may be stored somewhere in the system 100. The system 100 may include one or more processors, high-speed memory, hard disk storage and backup, network interfaces and protocols, input devices for data entry, and output devices for display, printing, And hardware elements necessary for the operations described herein. Figure 12 provides further details regarding these components.

12 is a block diagram illustrating components of an exemplary machine that can read instructions from a machine-readable medium and execute those instructions in the processor. 12 illustrates an exemplary form of a computer system 1200 in which instructions 1224 (e.g., software) that cause a machine to perform any one or more of the methods discussed herein may be executed. Lt; RTI ID = 0.0 > of < / RTI > In alternate embodiments, the machine may operate as a standalone device or may be connected (e.g., networked) with other machines. In a networked deployment, the machine may operate as a peer machine in a peer-to-peer (or distributed) network environment, or in the capabilities of a server machine or client machine in a server client network environment.

The machine may be a server computer, a client computer, a personal computer (PC), a tablet PC, a set top box (STB), a personal digital assistant (PDA), a cellular phone, a smart phone, a web device, a network router, a switch or a bridge, And may be any machine capable of executing instructions 1224 (sequential or otherwise) that specify actions to be taken by the processor. Also, although only one machine is shown, the term "machine" also includes any set of machines that execute instructions 1224 individually or collectively to perform any one or more of the methods described herein As shown in FIG.

Exemplary computer system 1200 includes a processor 1202 configured to communicate with one another via a bus 1208 (e.g., a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (ASICs), or one or more radio frequency integrated circuits (RFICs), or any combination thereof), main memory 1204, and static memory 1206. The computer system 1200 may further include a graphic display unit 1210 (e.g., a plasma display panel (PDP), a liquid crystal display (LCD), a projector, or a cathode ray tube (CRT)). Computer system 1200 also includes an alphanumeric input device 1212 (e.g., a keyboard), a cursor control device 1214 (e.g., a mouse, trackball, joystick, motion sensor Or other pointing device), a data store 1216, a signal generating device 1218 (e.g., a speaker), an audio input device 1226 (e.g., a microphone) and a network interface device 1220 can do.

Data store 1216 includes machine readable medium 1222 having stored thereon instructions 1224 (e.g., software) that implement any one or more of the methods and functions described herein. The instructions 1224 (e.g., software) may be stored in the main memory 1204 during its execution by the computer system 1200, main memory 1204 and processor 1202, which also comprise a machine- May also reside completely or at least partially within processor 1202 (e.g., in a cache memory of the processor). The instructions 1224 (e.g., software) may be transmitted or received via a network (not shown) via the network interface 1220.

Although the machine readable medium 1222 is depicted in the exemplary embodiment as a single medium, the term "machine readable medium" refers to a medium or medium (e.g., a computer readable medium) that can store instructions For example, a centralized or distributed database, or associated caches and servers). The term "machine-readable medium" refers to any medium that may store instructions (e.g., instructions 1224) for execution by a machine and that may cause the machine to perform any one or more of the methods It will also be taken to include the medium. The term "machine readable medium" includes, but is not limited to, data storage in the form of solid state memory, optical media, and magnetic media.

Some portions of the above description illustrate embodiments in terms of algorithms and symbolic representations of operations on information. These algorithmic descriptions and representations are commonly used by those of ordinary skill in the data processing arts to convey the essentials of their study to those of ordinary skill in the art. Functional, computational, or logical description, it is understood that these operations may be implemented by a computer program executed by a processor, equivalent electrical circuitry, microcode, or the like. In addition, it has also proved sometimes convenient to refer to these arrangements of operations as modules without loss of generality. The operations described and their associated modules may be implemented in software, firmware, hardware, or any combination thereof.

Any reference to "an embodiment" or "an embodiment" as used herein means that a particular element, feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment do. The appearances of the phrase "in one embodiment" in various places in this specification are not necessarily all referring to the same embodiment.

As used herein, the terms "comprises", "comprising", "includes", "including", "has", " Having "or any other variation thereof is intended to cover a non-exclusive inclusion. For example, a process, method, article, or apparatus that comprises a list of elements is not necessarily limited to those elements and may include other elements not expressly listed or inherent to such process, method, article, or apparatus . Unless otherwise expressly stated, "or" refers to an inclusive or not to an exclusive or. For example, condition A or B is satisfied by any one of the following: A is true (or is present), B is false (not present), A is false (or not present) True (or present), and both A and B are true (or present).

Also, the use of the singular representation ("a" or "an") is used to describe the elements and components of the embodiments of the present disclosure. This is merely for convenience and gives the general meaning of the invention. This description should be read to include one or at least one, and the singular also includes the plural unless it is explicitly meant otherwise.

Those of ordinary skill in the art will still recognize additional alternative structural and functional designs for the system and processes for providing generalized electronic magazines through the principles disclosed herein will be. Thus, while specific embodiments and applications have been shown and described, it will be appreciated that the disclosed embodiments are not limited to precise configuration and components disclosed herein. Various modifications, changes, and variations that will become apparent to those of ordinary skill in the art can be made in the arrangement, operation and details of the methods and apparatus disclosed herein without departing from the spirit and scope of the appended claims.

Claims (39)

A method for displaying news content to a user,
For each of a plurality of news content items, the computer:
Annotating the news content item with at least one topic and at least one date associated with the content of the item;
Storing an indication of each annotated item and associated annotations;
Maintaining, for each of the news content items, a count indicating the number of times the content item is viewed;
For each of the plurality of users, by a computer:
Identifying profile information for the user, the profile information including a plurality of news sources of interest to the user;
Receiving, by the computer, a time frame of interest and a subject of interest;
Identifying a plurality of news content items to recommend to one of the users from the annotated news content items and the profile information, wherein each news content item is annotated corresponding to the topic of interest A topic, and a date in the received time frame of interest, the content items being selected at least in part according to their associated view count; And
Recommending the news contents items to the user
≪ / RTI > The method according to claim 1,
Annotating each of the plurality of news content items to at least one location; And
Receiving, by the computer, a location of interest;
Further comprising:
Wherein the identified news content items have annotated locations corresponding to the location of interest. 3. The method of claim 2,
The step of annotating the news content items comprises:
Receiving, by the indexer, the news content item;
Determining, by the topic analyzer, at least one topic associated with the news content item;
Determining, by a geolocator module, at least one location associated with the news content item; And
Annotating the news content item with the determined topics and the determined locations
≪ / RTI > 3. The method of claim 2,
Wherein identifying the profile information for the user comprises:
Determining a location of the user; And
Identifying the determined location as a location of interest of the user
≪ / RTI > 3. The method of claim 2,
Wherein the step of recommending the news content item to the user comprises:
Displaying, in a first area of the user interface on the user device, an indication of a plurality of recommended content items; And
Displaying a map in a second area of the user interface, the map including a marker indicating a location associated with each of the recommended content items;
≪ / RTI > 6. The method of claim 5,
Receiving a user input identifying a recommended content item of one of the displayed recommended content items; And
In response to the received user input, highlighting a display of a marker indicative of the location of the identified content item
≪ / RTI > The method according to claim 6,
And removing the recommended content items not identified by the user input from the display. 6. The method of claim 5,
Receiving a user input identifying a marker of one of the displayed markers; And
In response to receiving the user input, removing the recommended content items not associated with the identified marker from the display
≪ / RTI > The method according to claim 1,
Receiving a selection by the user of an indication of one of the recommended content items; And
Instructing the user device to display the displayed recommended content item
≪ / RTI > The method according to claim 1,
Wherein the step of recommending the news content item to the user comprises:
Displaying, in a first area of the user interface on the user device, an indication of a plurality of recommended content items; And
Displaying a timeline in a second area of the user interface, the timeline including a marker indicating a date along a timeline associated with each of the recommended content items;
≪ / RTI > 11. The method of claim 10,
Receiving a user input identifying a recommended content item of one of the displayed recommended content items; And
In response to the received user input, highlighting a display of a marker indicating the date of the identified content item
≪ / RTI > 12. The method of claim 11,
And removing the recommended content items not identified by the user input from the display. 11. The method of claim 10,
Receiving a user input identifying a marker of one of the displayed markers; And
In response to receiving the user input, removing the recommended content items not associated with the identified marker from the display
≪ / RTI > 11. A computer program product for displaying news content to a user, the computer program product being stored on a non-volatile computer readable medium,
Instructions configured to cause the processor to perform steps,
The steps,
For each of a plurality of news content items, the computer:
Annotating the news content item with at least one topic and at least one date associated with the content of the item;
Storing an indication of each annotated item and associated annotations;
Maintaining, for each of the news content items, a count indicating the number of times the content item is viewed;
For each of the plurality of users, by a computer:
Identifying profile information for the user, the profile information including a plurality of news sources of interest to the user;
Receiving, by the computer, a time frame of interest and a subject of interest;
Identifying a plurality of news content items to recommend to one of the users from the annotated news content items and the profile information, wherein each news content item is annotated corresponding to the topic of interest A topic, and a date in the received time frame of interest, the content items being selected at least in part according to their associated view count; And
Recommending the news content items to the user
≪ / RTI > 15. The method of claim 14,
Instructions for receiving a selection by the user of an indication of one of the recommended content items; And
Instructions for instructing the user device to display the displayed recommended content item
≪ / RTI > 15. The method of claim 14,
The recommendation of the news contents item to the user,
Displaying in the first area of the user interface on the user device an indication of a plurality of recommended content items; And
Displaying a timeline in a second area of the user interface, the timeline including a marker indicating a date along a timeline associated with each of the recommended content items;
≪ / RTI > 17. The method of claim 16,
Instructions for receiving a user input identifying one recommended content item of the displayed recommended content items; And
In response to the received user input, instructions for highlighting the display of the marker indicating the date of the identified content item
≪ / RTI > 18. The method of claim 17,
Further comprising instructions for removing the recommended content items that are not identified by the user input from the display. 17. The method of claim 16,
Instructions for receiving a user input identifying a marker of one of the displayed markers; And
In response to receiving the user input, instructions for removing the recommended content items not associated with the identified marker from the display
≪ / RTI > A method for displaying news content to a user,
For each of a plurality of news content items, the computer:
Annotating the news content item with at least one topic and at least one location associated with the content of the item;
Storing an indication of each annotated item and associated annotations;
For each of the plurality of users, by a computer:
Identifying profile information for the user, the profile information including a plurality of topics of interest to the user and at least one location of interest of the user;
Identifying a news content item to be recommended to one of the users from the annotated news content items and the profile information; And
Recommending the news content item to the user
≪ / RTI > 21. The method of claim 20,
The step of annotating the news content items comprises:
Receiving, by the indexer, the news content item;
Determining, by the topic analyzer, at least one topic associated with the news content item;
Determining, by the geo-locator module, at least one location associated with the news content item; And
Annotating the news content item with the determined topics and the determined locations
≪ / RTI > 21. The method of claim 20,
Wherein identifying the profile information for the user comprises:
Determining a location of the user; And
Identifying the determined location as a location of interest of the user
≪ / RTI > 21. The method of claim 20,
Wherein identifying the profile information for the user comprises:
Receiving a location specified by the user; And
Identifying the received location as a location of interest of the user
≪ / RTI > 21. The method of claim 20,
Wherein the step of recommending the news content item to the user comprises:
Displaying, in a first area of the user interface on the user device, an indication of a plurality of recommended content items; And
Displaying a map in a second area of the user interface, the map including a marker indicating a location associated with each of the recommended content items;
≪ / RTI > 25. The method of claim 24,
Receiving a user input identifying a recommended content item of one of the displayed recommended content items; And
In response to the received user input, highlighting a display of a marker indicative of the location of the identified content item
≪ / RTI > 26. The method of claim 25,
And removing the recommended content items not identified by the user input from the display. 25. The method of claim 24,
Receiving a user input identifying a marker of one of the displayed markers; And
In response to receiving the user input, removing the recommended content items not associated with the identified marker from the display
≪ / RTI > 21. The method of claim 20,
Receiving a selection by the user of an indication of one of the recommended content items; And
Instructing the user device to display the displayed recommended content item
≪ / RTI > 11. A computer program product for displaying news content to a user, the computer program product being stored on a non-volatile computer readable medium,
Instructions configured to cause the processor to perform steps,
The steps,
For each of the plurality of news content items:
Annotating the news content item with at least one topic and at least one location associated with the content of the item;
Storing an indication of each annotated item and associated annotations;
For each of the plurality of users:
Identifying profile information for the user, the profile information including a plurality of topics of interest to the user and at least one location of interest of the user;
Identifying a news content item to recommend to one of the users from the annotated news content items and the profile information; And
Recommending the news content item to the user
≪ / RTI > 30. The method of claim 29,
Annotating the news content items may include:
Receiving, by the indexer, the news content item;
Determining, by the topic analyzer, at least one topic associated with the news content item;
Determining, by the geo-locator module, at least one location associated with the news content item; And
Annotating the news content item with the determined topics and the determined locations
≪ / RTI > 30. The method of claim 29,
Identifying the profile information for the user,
Determining a position of the user; And
Identifying the determined location as a location of interest of the user
≪ / RTI > 30. The method of claim 29,
Identifying the profile information for the user,
Receiving a location specified by the user; And
Identifying the received location as a location of interest of the user
≪ / RTI > 30. The method of claim 29,
The recommendation of the news contents item to the user,
Displaying in the first area of the user interface on the user device an indication of a plurality of recommended content items; And
Displaying a map in a second area of the user interface, the map including a marker indicating a location associated with each of the recommended content items;
≪ / RTI > 34. The method of claim 33,
Receiving a user input identifying one recommended content item of the displayed recommended content items; And
In response to the received user input, highlighting the display of the marker indicating the location of the identified content item
≪ / RTI > 35. The method of claim 34,
And removing the recommended content items not identified by the user input from the display. 34. The method of claim 33,
Receiving a user input identifying a marker of the displayed markers; And
In response to receiving the user input, removing the recommended content items not associated with the identified marker from the display
≪ / RTI > 30. The method of claim 29,
Receiving a selection by the user of an indication of one of the recommended content items; And
Instructing the user device to display the displayed recommended content item
≪ / RTI > A system for recommending news content to a user,
A processor;
An ingest module executed by the processor, the ingest module, for each of the plurality of news content items,
Annotating the news content item with at least one topic and at least one location associated with the content of the item;
To store an indication of each annotated item and associated annotations
Configured -;
A profile engine, executed by the processor, coupled to the ingest module, the profile engine configured to identify profile information for the user for each of a plurality of users, the profile information comprising a plurality of topics, And at least one location that is of interest to the user;
A recommendation generator, executed by the processor, coupled to the profile engine, the recommendation generator configured to identify, from the annotated news content items and the profile information, a plurality of news content items to recommend to one of the users; And
A news delivery module that is executed by the processor and is coupled to the recommendation engine and is adapted to recommend the news content items to the user,
≪ / RTI > 39. The method of claim 38,
Further comprising a map engine executed by the processor and coupled to the news delivery module,
The map engine,
Displaying a map on a user device, the map including markers associated with at least one of the recommended news content items;
Receive a specification of a new geographic location from the user device;
In response to receiving the request, obtaining a second plurality of news content items to recommend to the user from the recommendation generator, the second plurality of news content items including news content items related to the new geographical location -;
To display an updated map including the new geographic location and a marker associated with at least one of the recommended second plurality of news content items
System.

Images