From d3ec01b1461592a8e3ac2e8e38a4e6611643c5a1 2016-02-10 03:14:54
From: Gebrekirstos Gebremeskel <destinycome@gmail.com>
Date: 2016-02-10 03:14:54
Subject: [PATCH] update

---

diff --git a/main.tex b/main.tex
index 8857de042f7a65888130322245b76bbf00f6c60d..389565fc26b833d1a5dc556722bd90239bb673d2 100644
--- a/main.tex
+++ b/main.tex
@@ -464,7 +464,10 @@ Question for myself: Is it maybe possible to compute the category CTR's? Like a
 
 \section{discussion and conclusion}
 
-An idea, maybe show the variance of the categories in terms of their CTR? Another thing we can do is to explore the high achieving base itemsand the high achiving recommended itesm and see if they are some how the same items. We also do similar thing with lowe achving base item and recommended items. Is this holds, then clearly it indicates that a big factor is not about the current context, but just the nature of the items themselves, both ion the base items, and in the recommended items.  This is going to gold , as it already shows in the groups. But, we can also zoom in on the politics items and see if that holds too. Another thing we can consider is find base items and recommended items with big variance and study them with the view to finding the causes in terms of categories and also in terms of contenet. The variance of a recommendation item tells us information that is it is recommended to some values it makes sense, but if to others, it does not. This can also be studied at a particlat group's items, for example of politics. 
+In this study, we examined the factors that result in clicks on recommendation. Analysis was conducted at categoruies, transition between categories, and ites-levels. We found that clicks on recommendations are affected by both the item the user is reading and the recommended items. 
+
+
+% An idea, maybe show the variance of the categories in terms of their CTR? Another thing we can do is to explore the high achieving base itemsand the high achiving recommended itesm and see if they are some how the same items. We also do similar thing with lowe achving base item and recommended items. Is this holds, then clearly it indicates that a big factor is not about the current context, but just the nature of the items themselves, both ion the base items, and in the recommended items.  This is going to gold , as it already shows in the groups. But, we can also zoom in on the politics items and see if that holds too. Another thing we can consider is find base items and recommended items with big variance and study them with the view to finding the causes in terms of categories and also in terms of contenet. The variance of a recommendation item tells us information that is it is recommended to some values it makes sense, but if to others, it does not. This can also be studied at a particlat group's items, for example of politics. 
 
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