Wiki source code of Utilities - Recommendations

Last modified by Admin on 2023/02/14 10:17

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10.1	4	Before setting up your content recommendations please be sure to complete the step-by-step initial configuration process in [[Config Manager>>doc:Utilities - Configuration Manager]].
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11.1	8	Let’s Create a Content Recommendation Template! To access the Content Recommendation function click ACTIVATION, and then click Recommendations. **
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11.1	11	[[image:attach:Screen Shot 2022-02-04 at 4.59.21 PM.png\|\|thumbnail="true" height="138"]]
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9.1	13	Your web browser will load a new where you can start the content recommendation process. To begin, click the button Create Recommendation. If you did not mean to arrive at this page click Go back to go back to the last page viewed, otherwise proceed by clicking the Create Recommendation button.
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9.1	15	**[[image:attach:image2018-6-27 21:36:30.png\|\|height="150"]]
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	21	You will now see a Create Recommendation screen, with three subheadings underneath for each step, Definition, Algorithms, and Design. All steps are required!
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	23	~ [[image:attach:image2018-6-27 21:37:39.png\|\|height="400"]]
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5.1	25	= Definition =
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	27	Starting from the Definition tab, fill in the Title box. Enter a title (//i.e: Sports Entertainment). //This describes the type of content ads, or articles ONEcount will recommend to known or unknown users browsing content. Next, if desired, type a brief summary in the Description box to describe what tactics will be used in this recommendation widget.
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	29	If you want to limit the widget to a specific domain or domains, the domain name (//i.e: [[one-count.com>>url:http://one-count.com\|\|shape="rect"]])//.
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	31	Status can be Active or Disabled, when Status is Active this Content Recommendation will be visible to your users. When Disabled, it will not. If you are planning to use this recommendation now, make the Status Active. Proceed to the next phased by clicking the subheading Algorithm, do not click Save yet.
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5.1	33	= Algorithm =
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	35	Algorithm prioritizes content based onuser behavior and or behavior of other users in regards to the content being recommended (i.e: a user). Boosting level sets the priority, or “weight” of recommended content based on the specific algorithm chosen. A definition of the different algorithms used is below:
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8.1	39	[[image:attach:image2018-7-5 17:20:23.png]]
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8.1	41	Click Add to define the algorithms that will be used in this widget. Choose from one of the following options:
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1.1	43	1. Trending – Content that is being viewed the most during a given time period, ie., most-popular
	44	1. Look Alike Content– This algorithm recommends content to a user based on what other users with similar profiles are reading.
	45	1. Latest – Refers to content from newest pages being created.
	46	1. Collaborative Filtering – This is based on the amount of content read by the user on a specific topic, combined with the behavior of similar users (ie., look-alikes) on similar topics.
	47	1. Similar Interest – Content is based on the user’s past reading history. Recommendations are produced based on the articles that the user has already read.
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	49	Other Options: If “Ignore previously read items” is switched to “//On”//, all previously read items will not be recommended to the user again. If switched to “//Off”//, content may be recommended to the user again despite if they have read it before.
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11.1	51	For information on how ONEcount understands your content, click here: [[doc:OD.Content Keywords: How ONEcount Understands Your Content]]
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1.1	53	Proceed to the next phased by clicking the subheading Design, do not click Save yet.
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5.1	59	= Design =
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9.1	61	Design will allow real-time styling using CSS and a real-time view of changes styling made to content that will be presented to users.
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9.1	65	The Number of items will set the number/limit of articles that will be presented as recommended content per page the user views.
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9.1	67	Display title is a phrase (//i.e: “You might also like”, “People like you also liked”, “Trending articles on our site”//) emphasizing additional content the user may like.
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	71	Lastly, the styling of articles (CSS) can be modified by changing/adding/removing text within the CSS box on the right side.
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9.1	75	For example, locate the //“.cr-item-title {”// text starting at line 23. Click the end of the text “line-height: 1.5rem;” and hit enter so you land on a new blank line. Type “ __background-color: yellow;__ ” exactly as underlined and you will see that your new code will resemble all other code within the CSS box.
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9.1	77	You will also see your Preview articles change below. If your feeling ambitious, create another new line after “width: 250px” and enter “box-shadow: 10px 5px 10px 5px; “ and observe changes you’ve made below.
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9.1	79	You can only modify CSS here, the HTML code on the left will be generated by ONEcount.. You may now click Save to complete the content recommendation creation process.
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9.1	81	You will be presented with this message: Successfully added a recommendation.
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	83	[[image:attach:image2018-6-27 21:41:52.png\|\|height="400"]]
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	85	You can view information about your content recommendation:
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9.1	87	1. Search: Allows you to search for a Content Recommendation you’ve created in the past.
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9.1	89	2. Sort By: Allows you to sort through your Content Recommendations by Title or ID.
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9.1	91	3. Desc/Asc: Allows you to sort your recommendations in ascending or descending order.
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9.1	93	4. Rows: Will set the number of recommendations visible on-screen, the options are 10, 50, 100, and 150.
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9.1	95	5. Apply: Will execute the search criteria you’ve set in Search, Sort by and Rows.
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9.1	97	6. Reset: Will reset the search criteria back to default settings (Search is blank, Sort by is Title and Asc, and Rows are 10)
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9.1	99	7. Expansion Arrow: (Click this icon) Will expand into the Known/Unknown Recommendation Hit Ratio window.
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9.1	101	Known hit ratio: This is Content Recommendations made to users who are known.
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9.1	103	Unknown hit ratio: This is Content Recommendations made to users who are unknown.
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9.1	105	8. Edits: Will allow changes to be made to a Content Recommendation in its entirety with exception to its IDs which is automatically created.
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9.1	107	9. Delete: Will delete a Content Recommendation.
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