Tie does quite a bit, without it only the highest weighted field that has the term will be included in relevance score. Tie let's you include the other fields that match as well. On Mar 18, 2016 10:40 AM, "Robert Brown" <r...@intelcompute.com> wrote:
> Thanks for the added input. > > I'll certainly look into the machine learning aspect, will be good to put > some basic knowledge I have into practice. > > I'd been led to believe the tie parameter didn't actually do a lot. :-/ > > > > On 03/18/2016 12:07 PM, Nick Vasilyev wrote: > >> I work with a similar catalog; except our data is especially bad. We've >> found that several things helped: >> >> - Item level grouping (group same item sold by multiple vendors). Rank >> items with more vendors a bit higher. >> - Include a boost function for other attributes, such as an original image >> of the product >> - Rank items a bit higher if they have data from an external catalog like >> IceCat >> - For relevance and performance, we have several fields that we copy data >> into. High value fields get copied into a high weighted field, while lower >> value fields like description get copied into a lower weighted field. >> These >> fields are the backbone of our qf parameter, with other fields adding >> additional boost. >> - Play around with the tie parameter for edismax, we found that it makes >> quite a big difference. >> >> Hope this helps. >> >> On Fri, Mar 18, 2016 at 6:19 AM, Alessandro Benedetti < >> abenede...@apache.org >> >>> wrote: >>> In a relevancy problem I would repeat what my colleagues already pointed >>> out : >>> Data is key. We need to understand first of all our data before we can >>> understand what is relevant and what is not. >>> Once we specify a groundfloor which make sense ( and your basic approach >>> + >>> proper schema configuration as suggested + properly configured request >>> handler , seems a good start to me ) . >>> >>> At this point if you are still not happy with the relevancy (i.e. you are >>> not happy with the different boosts you assigned ) my strongest >>> suggestion >>> at this time is to move to machine learning. >>> You need a good amount of data to feed the learner and make it your Super >>> Business Expert) . >>> I have been recently working with the Learn To Rank Bloomberg Plugin [1] >>> . >>> In my opinion will be key for all the business that have many features >>> in >>> the game, that can help to evaluate a proper ranking. >>> For that you need to be able to collect and process signals, and you need >>> to carefully tune the features of your interest. >>> But the results could be surprising . >>> >>> [1] https://issues.apache.org/jira/browse/SOLR-8542 >>> [2] Learning to Rank in Solr < >>> https://www.youtube.com/watch?v=M7BKwJoh96s> >>> >>> Cheers >>> >>> On Thu, Mar 17, 2016 at 10:15 AM, Robert Brown <r...@intelcompute.com> >>> wrote: >>> >>> Thanks Scott and John, >>>> >>>> As luck would have it I've got a PhD graduate coming for an interview >>>> today, who just happened to do her research thesis on information >>>> >>> retrieval >>> >>>> with quantum theory and machine learning :) >>>> >>>> John, it sounds like you're describing my system! Shopping products >>>> from >>>> multiple sources. (De-duplication is going to be fun soon). >>>> >>>> I already copy fields like merchant, brand, category, to string fields >>>> to >>>> use them as facets/filters. I was contemplating removing the >>>> description >>>> due to the spammy issue you mentioned, I didn't know about the >>>> RemoveDuplicatesTokenFilterFactory, so I'm sure that's going to be a >>>> huge >>>> help. >>>> >>>> Thanks a lot, >>>> Rob >>>> >>>> >>>> >>>> On 03/17/2016 10:01 AM, John Smith wrote: >>>> >>>> Hi, >>>>> >>>>> For once I might be of some help: I've had a similar configuration >>>>> (large set of products from various sources). It's very difficult to >>>>> find the right balance between all parameters and requires a lot of >>>>> tweaking, most often in the dark unfortunately. >>>>> >>>>> What I've found is that omitNorms=true is a real breakthrough: without >>>>> it results tend to favor small texts, which is not what's wanted for >>>>> product names. I also added a RemoveDuplicatesTokenFilterFactory for >>>>> the >>>>> name as it's a common practice for spammers to repeat some key words in >>>>> order to be better placed in results. Stemming and custom stop words >>>>> (e.g. "cheap", "sale", ...) are other potential ideas. >>>>> >>>>> I've also ended up in removing the description field as it's often too >>>>> broad, and name is now the only field left: brand, category and >>>>> merchant >>>>> (as well as other fields) are offered as additional filters using >>>>> facets. Note that you'd have to re-index them as plain strings. >>>>> >>>>> It's more difficult to achieve but popularity boost can also be useful: >>>>> you can measure it by sales or by number of clicks. I use a combination >>>>> of both, and store those values using partial updates. >>>>> >>>>> Hope it helps, >>>>> John >>>>> >>>>> >>>>> On 17/03/16 09:36, Robert Brown wrote: >>>>> >>>>> Hi, >>>>>> >>>>>> I currently have an index of ~50m docs representing shopping products: >>>>>> name, description, brand, category, etc. >>>>>> >>>>>> Our "qf" is currently setup as: >>>>>> >>>>>> name^5 >>>>>> brand^2 >>>>>> category^3 >>>>>> merchant^2 >>>>>> description^1 >>>>>> >>>>>> mm: 100% >>>>>> ps: 5 >>>>>> >>>>>> I'm getting complaints from the business concerning relevancy, and was >>>>>> hoping to get some constructive ideas/thoughts on whether these boosts >>>>>> look semi-sensible or not, I think they were put in place pretty much >>>>>> at random. >>>>>> >>>>>> I know it's going to be a case of rounds upon rounds of testing, but >>>>>> maybe there's a good starting point that will save me some time? >>>>>> >>>>>> My initial thoughts right now are to actually just search on the name >>>>>> field, and maybe the brand (for things like "Apple Ipod"). >>>>>> >>>>>> Has anyone got a similar setup that could share some direction? >>>>>> >>>>>> Many Thanks, >>>>>> Rob >>>>>> >>>>>> >>>>>> >>> -- >>> -------------------------- >>> >>> Benedetti Alessandro >>> Visiting card : http://about.me/alessandro_benedetti >>> >>> "Tyger, tyger burning bright >>> In the forests of the night, >>> What immortal hand or eye >>> Could frame thy fearful symmetry?" >>> >>> William Blake - Songs of Experience -1794 England >>> >>> >
