By using Ranking method how to filter the most liked activity(or posts) in the getstream, and how to use the personalization?
Give some example related about ranking method and personalization
I have tried the examples given in the documentations but i can't understand what is that filtering?
personalization is a different level from ranking. Here's a description of personalization.
For ranking, take a look at this post to get ideas: https://getstream.io/blog/getting-started-ranked-feeds-getstream-io/
Related
I've been using Spark Item Similarity through mahout by following the steps in this article:
https://mahout.apache.org/users/algorithms/intro-cooccurrence-spark.html
I was able to clean my data, setup a local-only spark/hadoop node and all that.
Now, my question relies more in the interpretation of the matrices. I've tried some Google queries with limited success.
I'm creating a multi-modal recommender - and one of my datasets is very similar to the Mahout example.
Example input:
Customer ActionName Product
11064612 view 241505
11086047 purchase 110915
11121878 view CERT_DL
11149030 purchase CERT_FS
11104130 view 111401
The output of mahout is 2 sets of matrices. A similarity matrix and a coocurrence matrix.
This is my similarity matrix (I assume mahout uses my "filter1" purchases)
**791207-WP** 791520-WP:11.350536461453885 791520:9.547158147208393 76130142:7.938639976084232 711215:7.0641921646893024 751309:6.805891904514283
So how would I interpret this? If someone purchased 791207-WP they could be interested in 791520-WP? (so I'd use the left part against purchases of a customer and rank products in the right part?).
The row for 791520-WP looks like this:
791520-WP 76151220:18.954662238247693 791604-WP:13.951210170984268
So, in theory, I'd recommend 76151220 to someone who bought 791520-WP, correct?
Part 2 of the question is interpreting the cross-similarity matrix. Remember my filter2 is "views".
How would I interpret this:
**790907** 76120956:14.2824428207241 791500-LXQ2:13.864741460885853 190907:10.735807818360627
I take this matrix as "someone who visited the 76120956 web page ended up purchasing 790907". So I should promote 790907 to customers who bought 76120956 and maybe even add a link between these 2 products on our site, for example.
Or is it "people who visited the webpage of 790907 ended up buying 76120956"?
My plan is not to use these as-is. I'll still use RowSimilarity and different sources to rank products - but I'm missing the basic interpretation of the outputs from mahout.
If you know of any documentation that clarifies this, that would be a great asset to have.
Thank you.
In both cases the matrix is telling you that the item-id key is similar to the listed items by the LLR value attached to each similar item. Similar in the sense that similar users purchased the items. In the second case it is saying that similar people viewed the items and this view also appears to have led of a purchase of the same item.
Cooccurrence works for purchases alone, cross-occurrence adds the check to make sure the view also correlated with a purchase. This allows you to use both for recommendations.
The output is meant to be used with a search engine generally and you would use a user's history of purchases and views as a 2 field query against the matrices, one in each field.
There are analogous methods to find item-based recommendations.
Better yet, use something like the Universal Recommender here: actionml.com/docs/ur with PredictionIO for an end-to-end system.
I am trying to create an app that will help users find restaurants/movie theaters/malls/etc. to hang out based on ratings and distance. Other than just the place itself, I would also like to know more detailed information about the place. For example, if I were to look for parks, I would also like to know if theres a basketball or tennis court there. Ratings and popularity would also be an important aspect to prioritize suggestions.
After looking through all three of the APIs, I could not really find any substantial differences other than their search limits. Could anyone really differentiate each API for me? Maybe even recommend one based on my specific need?
Thanks!
The Foursquare API would fit this use case perfectly because you can supply very specific filters through the API. Also, they have extensive coverage around the world, unlike Google or Yelp.
I would check out the venues/explore endpoint and use a categoryId of Parks. You can use a query parameter of "basketball" or "tennis" to find parks that have courts for these.
How to filter activities in e.g. If I want to filter activity based on some content, it should list all the activities which had that content. Is there any such functionality provided by getstream?
Could you please suggest ?
I'm looking for the same thing. If we assume GetStream is like Facebook, Facebook doesn't really let you search their feed, and in general I think it's a tricky thing to do. What Facebook DOES do is have that SLOW search up at the top (you can tell it takes a long time and half the time doesn't even really have good results). If we accepted that our search would be slow we can paginate through a list of all the objects in our feed from GetStream then search through them on our site. Not a good solution but haven't really seen any other ones.
Is it possible to implement filtering on feeds in stream? I would like to allow users to follow other user posts but have those tagged with various categories. The desire is to select a category of Football and see just the posts made by people I follow which have that tag or potentially a collection of tags if the category was All Sports for example.
Looking in the api and docs it seems that a feed is pivoted on a single attribute so I can do a request for all posts of people I follow but not all posts for people I follow that are about NCAA or NFL.
Currently the getstream-io api does not have any filtering capability for the retrieval of activities. All possible options for retrieval of activities can be found in the REST docs
I found a number of similar questions on SO but they are all are either 2+ years old or aren't exactly what I am looking for.
All I would like to do is obtain a list of twitter users whose bio/profile contains certain terms (scientist, democrat, 'dog lover', etc.).
I've considered using a google site search but so far the results are incredibly noisy.
Any suggestions would be much appreciated!
CS
The Twitter API supports a People Search similar to the website's "Find on Twitter" search feature. Although you can not directly search using only profile descriptions, it appears that the description content is used as part of the search space. If you can think of a way to narrow down your results even further by directly searching the returned users' descriptions, you should be able to do what you're looking for. Check out the Twitter API documentation for more info.
Example:
Try searching for "husband father of three", and you get these results, which obviously are returned because of the profile descriptions.
I have used one tool to search twitter profiles using keywords and many advance filters. I love the information which has been provided by the FollowerSearch tool. The information was very specific, which helps me to analyze the public twitter profiles.
One of the best tools for quickly searching among the 800 million public Twitter accounts in the database is FollowerSearch.
With FollowerSearch, you can quickly conduct searches for Twitter influencers and Twitter bios across its massive database of more than 800 million Twitter profiles. You may look for Twitter profiles based on information like their location, line of work, number of followers, etc.
Twitter Influencer Profile Search
A Twitter bios search will assist you in simplifying the process, whether you're looking for influencers or new talent. You can discover Twitter folks who share your interests. Find out exact information on all the accounts whose bios contain your search term.
Identify key accounts and Twitter influencers that have required terms in their Twitter bios.
Look up new and budding talent.
Find Twitter users with similar interests.
Search Twitter profile or Search Twitter bios for any desired term.
I created a tool that does exactly what your looking for. Find70 let's you search for twitter profiles by their twitter bio. In fact, you can set up as many search filters as you want and define your own weighting for each filter. In your example above, you could search for: scientist, democrat, 'dog lover' and it would return all the accounts that have those in the bio. This can be combined with other filters too. Here it is http://www.find70.com/?t=stack