Combining topic suggestions from different topic sources to assign to textual data items

Abstract

Disclosed are systems, apparatus, methods and computer-readable storage media for combining topic suggestions from different topic sources to assign to textual data items. In some implementations, a first automated topic source provides one or more first topic suggestions to associate with a textual data item. Each first topic suggestion has a respective first characteristic, which can be adjusted. A second automated topic source provides one or more second topic suggestions to associate with the textual data item. Each second topic suggestion has a respective second characteristic, which can be adjusted. The first and second topic suggestions are combined to define a combined list. A reference value is determined or retrieved to impact ordering of the topic suggestions in the combined list.

What is claimed is: 
     
         1 . A computer implemented method for combining topic suggestions from different topic sources to assign to textual data items, the method comprising:
 receiving, from a first automated topic source, one or more first topic suggestions to associate with a textual data item, each first topic suggestion having a respective first characteristic;   adjusting, by a processor of a computing device, the first characteristic of each first topic suggestion;   receiving, from a second automated topic source, one or more second topic suggestions to associate with the textual data item, each second topic suggestion having a respective second characteristic;   adjusting the second characteristic of each second topic suggestion;   combining the first and second topic suggestions to define a combined list of topic suggestions;   providing the combined list of topic suggestions suitable for a display device capable of displaying the combined list in a user interface;   receiving, at the processor from the display device, a selection of one or more of the topic suggestions from the combined list to assign to the textual data item; and   determining or retrieving a reference value to impact ordering of the topic suggestions in the combined list.   
     
     
         2 . The method of  claim 1 , wherein the first characteristic is a first score, and the second characteristic is a second score. 
     
     
         3 . The method of  claim 2 , wherein:
 adjusting the first characteristic of each first topic suggestion includes applying a first weight to each scored first topic suggestion; and   adjusting the second characteristic of each second topic suggestion includes applying a second weight to each scored second topic suggestion, the first and second weights stored on a storage medium in communication with the processor.   
     
     
         4 . The method of  claim 3 , wherein the topic suggestions in the combined list are ordered according to weighted score. 
     
     
         5 . The method of  claim 3 , wherein the one or more first topic suggestions and the one or more second topic suggestions both include a common topic suggestion, and combining the first and second topic suggestions includes summing the respective weighted scores for the common topic suggestion. 
     
     
         6 . The method of  claim 3 , wherein the reference value is determined or retrieved by:
 determining or retrieving an average accept ratio, the average accept ratio being a ratio of a number of selected topic suggestions from the combined list to a number of total topic suggestions in the combined list;   determining or retrieving an accept ratio for each topic source, the accept ratio being a ratio of a number of selected topic suggestions from the topic source to a number of topic suggestions from the topic source; and   adjusting one or more of the weights stored on the storage medium according to a comparison of the accept ratio for a corresponding topic source with the average accept ratio.   
     
     
         7 . The method of  claim 6 , wherein adjusting a weight includes increasing or decreasing a previous value of the weight proportionally with respect to a control ratio of the accept ratio for the corresponding topic source to the average accept ratio. 
     
     
         8 . The method of  claim 7 , wherein the weight is increased when the control ratio is greater than one, and the weight is decreased when the control ratio is less than one. 
     
     
         9 . The method of  claim 7 , wherein the weight is adjusted from the previous value to a current value by applying the control ratio to the previous value. 
     
     
         10 . The method of  claim 7 , wherein an exponential factor is applied to the control ratio, the exponential factor governing a rate of the adjustment of the weight. 
     
     
         11 . The method of  claim 6 , wherein the average accept ratio and the accept ratio for each topic source are determined, and the one or more weights are adjusted, over a designated interval. 
     
     
         12 . The method of  claim 6 , wherein adjusting a weight includes increasing or decreasing a previous value of the weight proportionally with respect to the number of selected topic suggestions from the corresponding topic source. 
     
     
         13 . The method of  claim 6 , wherein adjusting a weight includes resetting the weight to a default value. 
     
     
         14 . The method of  claim 1 , further comprising:
 determining that the number of selected topic suggestions from the topic source meets or exceeds a threshold.   
     
     
         15 . The method of  claim 1 , wherein:
 each topic source is one of: a topic index, a natural language processing (NLP) library, a consecutive words identifier, a noun phrase extractor, and a use-based word identifier, and   the textual data item includes textual content and is one of: a social networking message, a database record, a feed-based record update, a document, a knowledge article, a scientific paper, a book, a web page, an online encyclopedia entry, a database record, a customer relationship management (CRM) object, a user profile, a group file, an email message, an instant message, and a text message.   
     
     
         16 . The method of  claim 1 , further comprising:
 associating the selected one or more topic suggestions with the textual data item, including updating a field in a database system storing the textual data item to indicate the association.   
     
     
         17 . The method of  claim 16 , wherein the textual data item is an information update, and the selected one or more topic suggestions are capable of being displayed in the user interface in conjunction with a social network feed including the information update. 
     
     
         18 . The method of  claim 1 , wherein the display device is one of: a smartphone, a laptop, a tablet, a wearable display device, a desktop computer, and a monitor. 
     
     
         19 . One or more computing devices for combining topic suggestions from different topic sources to assign to textual data items, the one or more computing devices comprising:
 one or more processors operable to execute one or more instructions to:
 receive, from a first automated topic source, one or more first topic suggestions to associate with a textual data item, each first topic suggestion having a respective first characteristic, 
 adjust the first characteristic of each first topic suggestion, 
 receive, from a second automated topic source, one or more second topic suggestions to associate with the textual data item, each second topic suggestion having a respective second characteristic, 
 adjust the second characteristic of each second topic suggestion, 
 combine the first and second topic suggestions to define a combined list of topic suggestions, and 
 determine or retrieve a reference value to impact ordering of the topic suggestions in the combined list. 
   
     
     
         20 . A non-transitory computer-readable storage medium storing instructions executable by a processor to cause a method to be performed for combining topic suggestions from different topic sources to assign to textual data items, the method comprising:
 receiving, from a first automated topic source, one or more first topic suggestions to associate with a textual data item, each first topic suggestion having a respective first characteristic;   adjusting the first characteristic of each first topic suggestion;   receiving, from a second automated topic source, one or more second topic suggestions to associate with the textual data item, each second topic suggestion having a respective second characteristic;   adjusting the second characteristic of each second topic suggestion;   combining the first and second topic suggestions to define a combined list of topic suggestions; and   determining or retrieving a reference value to impact ordering of the topic suggestions in the combined list.