Can any one suggest search engine that has flexible ranking calculation?
What is flexible ranking calculation?
for example I have two documents:
obj1 = {
title: "new record"
tags: [
{value:"tag1", weight:1},
{value:"tag2", weight:0.8},
{value:"tag3", weight:2},
]
}
obj2 = {
title: "new record with tag1 in title"
tags: [
{value:"tag1", weight:0.5},
{value:"tag2", weight:1},
{value:"tag3", weight:0.01},
]
}
let's assume weight for "title" property is 0.25
When I do search for "tag1" in all properties
I want search to return ranking = 1 for obj1 and ranking = 0.75 for obj2
I know Solr can do it but do you have any other suggestions?
You mention weight for title but then the values you described for scores mapped directly to tag values. Not sure if you missed a detail on how these two connect.
Assuming you want the score of the title match to play a role in the overall document score in addition to boosting documents that match a particular tag or value range, you can do this with Azure Search using scoring profiles (if you want a search-as-a-service solution), and can do it with Solr or Elasticsearch by including boosts as part of the query if you prefer to deploy and management your own infrastructure; in Elasticsearch for example there are function boosts that will allow you to use the value of a field as input to boost computation.
Related
How do I get random algolia item from it's index?
All of my items have:
objectID "POST#news#44.7704046#17.1900285"
name "News"
categories [ "cafe", "food", "establishment", "food" ]
_geoloc { lat: "44.7704046", lng: "17.1900285" }
I would like to optionally search by name, match 1 or all categories, geo location filtering with distance, and most importantly, I only want 1 RANDOM returned from Algolia.
I can't do client side random, because sometimes without filters I would get too many results back ( 10000 ), so I can't transfer that over the wire.
Please help
Hi #Djordje there are no real way to get a random result with Algolia though you you could use an attribute to randomise the results and only use the first item. See documentation [here][1]
I have a collection dinosaurs with documents of this structure:
doc#1:
name: "Tyrannosaurus rex",
dominantColors: [
"beige",
"blue",
"green"
]
doc#2:
name: "Velociraptor",
dominantColors: [
"green",
"orange",
"white"
]
I want to query the collection by color name (for example: green) to get documents sorted by color's position in dominantColors array. First get the documents in which green occurs higher in the array, then those in which it is lower. So, in the provided case I would get doc#2 first, then doc#1.
Each dominantColors array contains 3 elements, with elements sorted from most dominant to least.
I am looking through documentation, but am not able to find a solution. Maybe I need a different data structure altogether?
Cloud Firestore doesn't support querying arrays by ranked index. The only way you can query an array is using an array-contains type query.
What you could do instead is organize your colors using maps where the color is the key and their rank is the value:
name: "Tyrannosaurus rex",
dominantColors: {
"beige": 1,
"blue": 2,
"green": 3
}
Then you can order the query by the value of the map's property. So, in JavaScript, it would be something like this:
firebase
.collection('dinosaurs')
.where('dominantColors.green', '>', 0)
.orderBy('dominantColors.green')
Greeting,
let assume, I have one manufacture and 10 customers that manufacture create links with some of them randomly(I call these links "contract-links").
One of the properties of manufacture is "real-cost" and one of the properties of customers is "real-waiting-time". "real-waiting-time" is a clear number. Also, Assume service-cost as a global variable.
To calculate the "real-cost", I need the sum of "real-waiting-time" of customers who have links with the manufacture and then multiply in service cost.
I have a question here to calculate "real-cost". How can I call the "real-waiting-time" of all customers and then calculate the real-cost for manufacture?
manufactures-own [ final-costs]
customers-costs [ real-waiting-time]
contract-links [ the-real]
ask manufactures [
final-calculation-for-manufacture
]
to final-calculation-for-manufacture
let the-manufacture self
let the-contract my-contract-links
ask my-contract-links [
set the-real [real-waiting-time] of end2
]
let the-sum sum [ the-real] of my-contract-links
set final-cost the-sum * cost-service-slider
end
It gives me a number, but the answer is wrong.
I think the reason that you are getting the wrong number is that you are doing a lot of setting of the attribute values at the other end of the links instead of getting the information from that link. But your general approach is too complicated - if you have created a link breed called contract-links (which you seem to have), then the agents at the other ends of those links are the link neighbors of agent asking. Try something like this.
manufactures-own [ final-costs]
customers-costs [ real-waiting-time]
contract-links [ the-real]
ask manufactures
[ let the-sum final-costs sum [real-waiting-time] of contract-links-neighbors
set final-cost the-sum * cost-service-slider
]
end
This assumes you want the sum of the waiting times of the linked customers. I couldn't work out what the attribute the-real is for the links.
I have a documents contains list of location "boxes" (square area). Each box is represented by 2 points (bottom-left or south-west, top-right or north-east).
Document, for example:
{
locations: [
[[bottom,left],[top,right]],
[[bottom,left],[top,right]],
[[bottom,left],[top,right]]
]
}
I'm using 2d index for those boundaries points.
My input is a specific location point [x,y] and I want to fetch all documents that have at list one box that this point is located in it.
Is there any geospatial operator I can use to do that?
How do I write this query?
You can use the box operator, see:
http://docs.mongodb.org/manual/reference/operator/query/box/#op._S_box with the following example taken directly from that page:
db.places.find( { loc : { $geoWithin : { $box :
[ [ 0 , 0 ] ,
[ 100 , 100 ] ] } } } )
It is worth noting that the 2d index is considered legacy. If you can convert to using GeoJSON and a 2dsphere index, then you can use the $geoWithin operator: see
http://docs.mongodb.org/manual/reference/operator/query/geoWithin/#op._S_geoWithin
GeoJSON has a number of other benefits, not least of which, is that it is easily transmitted and digested by web mapping apps such as OpenLayers or Leaflet.
I am trying to order at list by nearest place. This is working fine with this code:
Cloud.Places.query({
page: 1,
per_page: 20,
where: {
lnglat: { '$nearSphere': [latitudefast,longitudefast], }
},
order: {
lnglat: { '$nearSphere': [latitudefast,longitudefast], }
},
latitudefast and longitudefast is representing the actual position on the user. It has be defined before the query.
But it is "upside down", which means that the nearest place is in the bottom of the list, and the one farthest away is at the top of the list! How come? How do I order in reverse? Am i ordering wrong?
Thanks!
Have you tried not specifying the order? $nearSphere by default returns results sorted by distance.
From MongoDB's documentation (which ACS uses as its data store) describing $near:
The above query finds the closest points to (50,50) and returns them
sorted by distance (there is no need for an additional sort
parameter).
This applies to $nearSphere as well.
http://www.mongodb.org/display/DOCS/Geospatial+Indexing