Implicit feedback - Revision history

Zeno Gantner: /* Prediction from Implicit Feedback */ fix some whitespace

2011-11-12T09:53:40Z

Prediction from Implicit Feedback: fix some whitespace

Zeno Gantner: /* See also */

2011-11-12T09:53:07Z

Zeno Gantner: /* Using Implicit Feedback */

2011-11-12T09:52:12Z

Using Implicit Feedback

Tqchen: /* Use Implicit Feedback */

2011-11-12T01:47:47Z

Use Implicit Feedback

Tqchen at 01:46, 12 November 2011

2011-11-12T01:46:49Z

Zeno Gantner at 10:14, 9 November 2011

2011-11-09T10:14:02Z

Zeno Gantner at 16:10, 10 August 2011

2011-08-10T16:10:14Z

Zeno Gantner: new page

2011-02-21T21:31:18Z

new page

New page

'''Implicit feedback''' is [[user]] activity that can be used to indirectly infer user [[preference]]s, e.g. clicks, page views, purchase actions. Sometimes only positive feedback is known, e.g. the products customers have bought, but not the ones they have decided against.

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 '''Implicit feedback''' is [[user]] activity that can be used to indirectly infer user [[preference]]s, e.g. clicks, page views, purchase actions. Sometimes only positive feedback is known, e.g. the products customers have bought, but not the ones they have decided against.
 == Prediction from Implicit Feedback ==
-Prediction from implicit feedback(implicit feedback ranking)
+Prediction from implicit feedback (implicit feedback ranking)
-refers to the task that ranks a list of item so that the items user prefer( more likely to click,view etc. ) will be in higher order.
+refers to the task that ranks a list of item so that the items user prefer (more likely to click, view etc.) will be in higher order.
 == Using Implicit Feedback ==

@@ Line 9: / Line 9: @@
 == See also ==
-* The [[MyMediaLite]] software supports [[item prediction]] from implicit feedback.
+* The [[MyMediaLite]] software supports [[item recommendation]] from implicit feedback.
-* The [[SVDFeature]] software supports prediction from implicit feedback and using implicit feedback to improve recommendation.
+* The [[SVDFeature]] software supports prediction from implicit feedback and using implicit feedback to improve rating prediction.
 == External links ==
 * [[Wikipedia: Implicit data collection]]

@@ Line 5: / Line 5: @@
 == Using Implicit Feedback ==
-Implicit feedback information can be used to enhance collaborative filtering algorithms. The most famous example is [[SVD++]]
+Implicit feedback information can be used to enhance [[collaborative filtering]] algorithms for [[rating prediction]].
 == See also ==

@@ Line 4: / Line 4: @@
 refers to the task that ranks a list of item so that the items user prefer( more likely to click,view etc. ) will be in higher order.
-== Use Implicit Feedback ==
+== Using Implicit Feedback ==
 Implicit feedback information can be used to enhance collaborative filtering algorithms. The most famous example is [[SVD++]]

@@ Line 1: / Line 1: @@
 '''Implicit feedback''' is [[user]] activity that can be used to indirectly infer user [[preference]]s, e.g. clicks, page views, purchase actions. Sometimes only positive feedback is known, e.g. the products customers have bought, but not the ones they have decided against.
 == See also ==
 * The [[MyMediaLite]] software supports [[item prediction]] from implicit feedback.
 == External links ==
 * [[Wikipedia: Implicit data collection]]

← Older revision		Revision as of 10:14, 9 November 2011
Line 3:		Line 3:
	== See also ==		== See also ==
	* The [[MyMediaLite]] software supports [[item prediction]] from implicit feedback.		* The [[MyMediaLite]] software supports [[item prediction]] from implicit feedback.
		+
		+	== External links ==
		+	* [[Wikipedia: Implicit data collection]]

← Older revision		Revision as of 16:10, 10 August 2011
Line 1:		Line 1:
	'''Implicit feedback''' is [[user]] activity that can be used to indirectly infer user [[preference]]s, e.g. clicks, page views, purchase actions. Sometimes only positive feedback is known, e.g. the products customers have bought, but not the ones they have decided against.		'''Implicit feedback''' is [[user]] activity that can be used to indirectly infer user [[preference]]s, e.g. clicks, page views, purchase actions. Sometimes only positive feedback is known, e.g. the products customers have bought, but not the ones they have decided against.
		+
		+	== See also ==
		+	* The [[MyMediaLite]] software supports [[item prediction]] from implicit feedback.