Author: ilnurkh

It is known about URL that it is shown too often with very low relevance (according to Bert and/or BM25)

Factor about the presence of a symbol '?' In Url. It is zero if the Url has CGI parameters (more precisely: all duplicate have a symbol '?' In Url).

The factor for telephone attributes Tel_Full from the original request text of the document. Algorithm for aggregation of the scales of words BOCM15. Normalization coefficient 0.01.

Yabarvisits Factor in the annotation index, QueryMatchpredical factor

Yabarvisits Factor in the annotation index, AnnotationMatchprediction factor

Yabartime factor in the annotation index, QueryMatchpredical factor

Yabartime Factor in the annotation index, AnnotationMatchpredical factor

Yabartime Factor in Annotacionnom Indexes, Factor AnnotationMatchpredictionWeighted

Equal to one if the page connects JS-API of any geo-data supplier

Bm15K01 factor over hits from Url

Bm15K01 factor over hits from Title

Bocm15K001 factor over hits from Title

Bm11Norm16384 factor over hits from Text

Bocm11Norm256 factor over hits from Text

CosineMatchMaxPrediction factor over hits from Text

Bm15FLogK0001 factor over hits from FieldSet1 stream

Bm15FLogK0001 factor over hits from FieldSet2 stream

BclmWeightedFLogW0K0001 factor over hits from FieldSet3 stream

Bm15FLogW0K00001 factor over hits from FieldSetUT stream

Chain0Wcm factor over hits from Body

PairMinProximity factor over hits from Body

MinWindowSize factor over hits from Body

CosineMatchMaxPrediction factor over hits from PopularSeFrcBrowser stream

MixMatchWeightedValue factor over hits from DoubleFrc stream

AnnotationMaxValueWeighted factor over hits from DoubleFrc stream

AnnotationMaxValue factor over hits from DoubleFrc stream

AnnotationMatchWeightedValue factor over hits from DoubleFrc stream

AllWcmWeightedValue factor over hits from DoubleFrc stream

AllWcmMatch95AvgValue factor over hits from DoubleFrc stream

AllWcmWeightedPrediction factor over hits from DoubleFrc stream

AllWcmMatch80AvgValue factor over hits from DoubleFrc stream

FullMatchValue factor over hits from DoubleFrc stream

FullMatchAnyValue factor over hits from DoubleFrc stream

ExactQueryMatchAvgValue factor over hits from DoubleFrc stream

BclmMixPlainKE5 factor over hits from OneClickFrcXfSp stream

Bm15StrictAnnotationK01 factor over hits from OneClickFrcXfSp stream

AllWcmWeightedValue factor over hits from OneClickFrcXfSp stream

AllWcmWeightedPrediction factor over hits from OneClickFrcXfSp stream

AllWcmMatch80AvgValue factor over hits from OneClickFrcXfSp stream

MixMatchWeightedValue factor over hits from OneClickFrcXfSp stream

AnnotationMatchWeightedValue factor over hits from OneClickFrcXfSp stream

BclmPlaneProximity1Bm15W0Size1K0001 factor over hits from OneClickFrcXfSp stream

BclmWeightedProximity1Bm15Size1K001 factor over hits from OneClickFrcXfSp stream

BclmMixPlainKE5 factor over hits from BQPRSample stream

AllWcmWeightedValue factor over hits from BQPRSample stream

AllWcmWeightedPrediction factor over hits from BQPRSample stream

AllWcmMaxPrediction factor over hits from BQPRSample stream

AllWcmMatch80AvgValue factor over hits from BQPRSample stream

MixMatchWeightedValue factor over hits from BQPRSample stream

CosineMatchMaxPrediction factor over hits from BQPRSample stream

AnnotationMaxValueWeighted factor over hits from BQPRSample stream

AnnotationMaxValue factor over hits from BQPRSample stream

AnnotationMatchWeightedValue factor over hits from BQPRSample stream

Bocm15K001 factor over hits from BQPRSample stream

BclmPlaneProximity1Bm15W0Size1K0001 factor over hits from BQPRSample stream

BclmWeightedProximity1Bm15Size1K001 factor over hits from BQPRSample stream

BclmPlaneProximity1Bm15W0Size1K0001 factor over hits from LongClickSP stream

Bm15MaxAnnotationK001 factor over hits from LongClickSP stream

FullMatchValue factor over hits from LongClickSP stream

MixMatchWeightedValue factor over hits from LongClickSP stream

CosineMatchMaxPrediction factor over hits from LongClickSP stream

AnnotationMaxValue factor over hits from LongClickSP stream

AnnotationMaxValueWeighted factor over hits from LongClickSP stream

AnnotationMatchWeightedValue factor over hits from LongClickSP stream

AllWcmMatch95AvgValue factor over hits from LongClickSP stream

AllWcmWeightedValue factor over hits from LongClickSP stream

AllWcmMaxMatch factor over hits from LongClickSP stream

AllWcmWeightedPrediction factor over hits from LongClickSP stream

Bocm15K001 factor over hits from LongClickSP stream

QueryPrefixMatchOriginalWordValue factor over hits from LongClickSP stream

BclmPlaneProximity1Bm15W0Size1K0001 factor over hits from SamplePeriodDayFrc stream

AttenV1Bm15K05 factor over hits from SamplePeriodDayFrc stream

FullMatchValue factor over hits from SamplePeriodDayFrc stream

FullMatchAnyValue factor over hits from SamplePeriodDayFrc stream

AllWcmWeightedValue factor over hits from SamplePeriodDayFrc stream

AllWcmWeightedPrediction factor over hits from SamplePeriodDayFrc stream

AllWcmMatch95AvgValue factor over hits from SamplePeriodDayFrc stream

AllWcmMatch80AvgValue factor over hits from SamplePeriodDayFrc stream

MixMatchWeightedValue factor over hits from SamplePeriodDayFrc stream

AnnotationMatchWeightedValue factor over hits from SamplePeriodDayFrc stream

AnnotationMaxValue factor over hits from SamplePeriodDayFrc stream

AnnotationMaxValueWeighted factor over hits from SamplePeriodDayFrc stream

Bocm15K001 factor over hits from SamplePeriodDayFrc stream

AllWcmWeightedValue factor over hits from CorrectedCtrXFactor stream

AllWcmMaxPrediction factor over hits from CorrectedCtrXFactor stream

AllWcmWeightedPrediction factor over hits from CorrectedCtrXFactor stream

AllWcmMatch80AvgValue factor over hits from CorrectedCtrXFactor stream

MixMatchWeightedValue factor over hits from CorrectedCtrXFactor stream

AnnotationMatchWeightedValue factor over hits from CorrectedCtrXFactor stream

BclmPlaneProximity1Bm15W0Size1K001 factor over hits from CorrectedCtrXFactor stream

BclmWeightedProximity1Bm15Size1K001 factor over hits from CorrectedCtrXFactor stream

AllWcmMaxPrediction factor over hits from LongClick stream

MixMatchWeightedValue factor over hits from LongClick stream

AnnotationMaxValueWeighted factor over hits from LongClick stream

FullMatchValue factor over hits from LongClick stream

AnnotationMatchWeightedValue factor over hits from LongClick stream

AllWcmWeightedValue factor over hits from SimpleClick stream

AllWcmWeightedPrediction factor over hits from SimpleClick stream

AllWcmMaxPrediction factor over hits from SimpleClick stream

MixMatchWeightedValue factor over hits from SimpleClick stream

AnnotationMatchWeightedValue factor over hits from SimpleClick stream

AnnotationMaxValueWeighted factor over hits from BrowserPageRank stream

AnnotationMatchWeightedValue factor over hits from BrowserPageRank stream

AnnotationMaxValue factor over hits from BrowserPageRank stream

Bocm15K001 factor over hits from BrowserPageRank stream

MixMatchWeightedValue factor over hits from OneClick stream

FullMatchValue factor over hits from OneClick stream

AnnotationMatchWeightedValue factor over hits from OneClick stream

AllWcmWeightedPrediction factor over hits from SplitDwellTime stream

Bm15MaxAnnotationK001 factor over hits from SplitDwellTime stream

BclmWeightedProximity1Bm15Size1K0001 factor over hits from QueryDwellTime stream

AttenV1Bm15K001 factor over hits from QueryDwellTime stream

MixMatchWeightedValue factor over hits from QueryDwellTime stream

AnnotationMaxValueWeighted factor over hits from QueryDwellTime stream

AnnotationMaxValue factor over hits from QueryDwellTime stream

AnnotationMatchWeightedValue factor over hits from QueryDwellTime stream

AllWcmWeightedValue factor over hits from QueryDwellTime stream

AllWcmMatch80AvgValue factor over hits from QueryDwellTime stream

BclmPlaneProximity1Bm15W0Size1K0001 factor over hits from RandomLogDBM35 stream

Bm15StrictAnnotationK001 factor over hits from RandomLogDBM35 stream

MixMatchWeightedValue factor over hits from RandomLogDBM35 stream

AnnotationMaxValueWeighted factor over hits from RandomLogDBM35 stream

AnnotationMatchWeightedValue factor over hits from RandomLogDBM35 stream

AllWcmWeightedValue factor over hits from RandomLogDBM35 stream

FullMatchValue factor over hits from RandomLogDBM35 stream

ExactQueryMatchAvgValue factor over hits from RandomLogDBM35 stream

Linguistic boosting factor. Type of extensions: XFDTSHOW. Factor: MixmatchweightedValue by Stream Querydwelltime. The maximum balanced value of the expansion factor.

Linguistic boosting factor. Type of extensions: XFDTSHOW. Factor: MixmatchweightedValue by Stream Querydwelltime. The average balanced value of the expansion factor.

Linguistic boosting factor. Type of extensions: XFDTSHOW. Factor: MixmatchweightedValue by Stream Querydwelltime. The minimum balanced value of the factor on the expansion top.

Linguistic boosting factor. Type of extensions: XFDTSHOW. Factor: AnnotationMatchWeightedValue by Stream Querydwelltime. The minimum balanced value of the factor on the expansion top.

Linguistic boosting factor. Type of extensions: XFDTSHOW. Factor: AnnotationMatchWeightedValue by Stream Querydwelltime. The maximum balanced value of the expansion factor.

Linguistic boosting factor. Type of extensions: XFDTSHOW. Factor: Allwcmmatch95Avgvalue Stream QueryDwellTime. The average balanced value of the factor on the expansion top.

Linguistic boosting factor. Type of extensions: XFDTSHOW. Factor: MixMatchweightedValue for Stream BQPRSAMPLE. The maximum balanced value of the expansion factor.

Linguistic boosting factor. Type of extensions: XFDTSHOW. Factor: MixMatchweightedValue in stream DoubleFrc. The maximum balanced value of the expansion factor.

The factor for the original request. It is considered to be toxicated by Ural. Algorithm Cosinematchmaxpredical.

The factor for the original request. It is considered to be toxicated by Ural. The weight of the hit is multiplied by 1/ (1 + the position of the word in the sentence) an algorithm for aggregation of the scales of words: BM15. Normalization coefficient 0.5.

The factor for the original request. It is considered according to the heading of the document. The algorithm for aggregation of words weights is BCLMMIXPLAIN: a linear mixture of annotation BCLM weights and balanced Positionless weights of the word, then the former meters are aggregated through BM15. Normalization coefficient 10^(-5).

The factor for the original request. It is considered according to the heading of the document. CMMATCHTOP5AVGMATCHVALUE algorithm.

The factor for the original request. It is considered according to the heading of the document. The degree of coating of the words of the request is accurate to the form (without synonyms).

The factor for the original request. It is considered according to the heading of the document. The weight of the hit is multiplied by 1/ (1 + the position of the word in the sentence) an algorithm for aggregation of the scales of words: BM15. Normalization coefficient 0.5.

The factor for the original request. It is considered according to the contents of the document. The algorithm for aggregation of words weights is BCLMMIXPLAIN: a linear mixture of annotation BCLM weights and balanced Positionless weights of the word, then the former meters are aggregated through BM15. Normalization coefficient 10^(-5).

The factor for the original request. It is considered according to the contents of the document. Algorithm Cosinematchmaxpredical.

The factor for the original request. It is considered according to the contents of the document. Algorithm Allwcmweightedpredical.

The factor for the original request. It is considered according to the contents of the document. Algorithm for aggregation of the scales of words BOCM15. Normalization coefficient 0.01.

The factor for the original request. It is considered according to the contents of the document. Algorithm: Querypartmatchsumvalueany.

The factor for the original request. It is considered according to the contents of the document. The degree of coating of the words of the request is accurate to the form (without synonyms).

The factor for the original request. It is considered according to the contents of the document. The degree of covering the words of the request in the exact form.

The factor for the original request. It is considered according to the contents of the document. Libra Agnregation algorithm: BM15Maxannotation normalization coefficient 0.01.

Linguistic boosting factor. Type of extensions: QFUF. Aggregation on all extensions. The greatest value of the factor. According to the stream from the lincum index of Linkannindicator. AnnotationmaxvalueWeighted algorithm - maximum weight (according to Mainweights Libra of Words) Operations coverage, weighed to the weight of the annotation

Linguistic boosting factor. Type of extensions: QFUF. Aggregation on all extensions. The greatest value of the factor. According to the stream from the lincum index of Linkannindicator. AnnotationmaxvalueWeighted algorithm - maximum weight (according to Mainweights Libra of Words) Operations coverage, weighed to the weight of the annotation

Linguistic boosting factor. Type of extensions: XFDTSHOW. Aggregation on all extensions. The greatest balanced value of the factor. It is normalized for the maximum weight of expansion. According to the stream from the lincum index of Linkannindicator. PerwordCmmaxMatchMin algorithm: The minimum according to CMMMAXMATCH weight.

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN (closest to the DSSM models trained to predict XFDTSHOW of extension). Aggregation on all extensions. The greatest balanced value of the factor. A mixture of many streams, weight is calculated by a fixed Polita component from the scales on this annotation. The algorithm for aggregation of words weights is BCLMMIXPLAIN: a linear mixture of annotation BCLM weights and balanced Positionless weights of the word, then the former meters are aggregated through BM15. Normalization coefficient 10^(-5).

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN (closest to the DSSM models trained to predict XFDTSHOW of extension). Aggregation on all extensions. The greatest balanced value of the factor. It is normalized for the maximum weight of expansion. Stream: Correctedctrlongperiod. The degree of coating of words query accurate to form (without synonyms).

Linguistic boosting factor. Type of extensions: QFUF. Aggregation on all extensions. The greatest balanced value of the factor. It is normalized for the maximum weight of expansion. The result of the VPCG for a long long period, data: CorrectedClicks. The average weight of the anntations among those in which the request was an accurate tuning.

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN (closest to the DSSM models trained to predict XFDTSHOW of extension). Aggregation on all extensions. The greatest balanced value of the factor. It is normalized for the maximum weight of expansion. Stream: Correctedctrlongperiod. The BCLMPLANEPROXIMITY15W0SIZE1 algorithm: uses BCLM with free weight if there are several words of the request, if the word is one, then the sum of hits is used like a coincidence. Normalization coefficient 0.001.

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN (closest to the DSSM models trained to predict XFDTSHOW of extension). Aggregation on all extensions. The average weight of extensions.

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN. Factor: BCLMWEIGHTEDFLOGW0 in the Stream group 3. The maximum balanced value of the factor.

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN. Factor: BM15FLOG in the group of streams 2. The maximum balanced value of the factor.

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN. Factor: ORIGINALREQUENTFRACTFRACTION OF THE FIELDSETBAGOFWORDS Stream.

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN. Factor: MixmatchweightedValue by Stream Querydwelltime. The maximum balanced value of the factor is normalized for the total weight.

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN. Factor: BM15 according to Stream Title. The total balanced values ​​of the factor multiplied by weight (\ frac {\ sum w_i * (w_i * f_i)} {\ sum w_i}) normalized for total weight.

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN. Factor: BCLMWEIGHTEDFLOGW0 in the Stream group 3. The minimum value of the factor for the expansion top.

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN. Factor: BCLMWEIGHTEDFLOGW0 in the Stream group 3. The total balanced values ​​of the factor multiplied by weight (\ frac {\ sum w_i * (w_i * f_i)} {\ sum w_i}) normalized for the total weight.

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN. Factor: BM15FLOG in the Stream group 1. The maximum balanced value of the factor.

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN. Factor: BM15FLOG in the Stream group 1. The total balanced value of the factor is normalized for the total weight.

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN. Factor: Bag AnnotationMatChavgvalue by Stream LongClicksp.

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN. Factor: BM15FLOG for the Stream group 1. The total balanced values ​​of the factor multiplied by weight (\ frac {\ sum w_i * (w_i * f_i)} {\ sum w_i}) for expansion top extensions, standardized for the total weight of the expansion top.

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN. Factor: BM15FLOG in the Stream group 1. The minimum balanced value of the factor for the expansion top extensions normalized for the maximum weight by the expansion top.

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN. Factor: PairminProximity according to Stream Body. The maximum balanced value of the factor is normalized for the total weight.

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN. Factor: BM15FLOG for the Stream group 1. The total balanced values ​​of the factor multiplied by weight (\ frac {\ sum w_i * (w_i * f_i)} {\ sum w_i}) normalized for total weight.

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN. Factor: SIMPLECLIC SIMPLECLICS bag.

Linguistic boosting factor. Type of extensions: XFDTSHOWKNN. Factor: CosinemaxMatch bag according to Title Stream.

Linguistic boosting factor. Type of extensions: Querytotextbyxfdtshowknn. Factor: Norm256 by stream BOCM11. The total balanced values ​​of the factor multiplied by weight (\ frac {\ sum w_i * (w_i * f_i)} {\ sum w_i}).

Linguistic boosting factor. Type of extensions: Querytotextbyxfdtshowknn. Factor: Minwindowsize by Stream Body. The total balanced values ​​of the factor multiplied by weight (\ frac {\ sum w_i * (w_i * f_i)} {\ sum w_i}) by the expansion top, normalized for the total weight according to the expansion top.

Linguistic boosting factor. Type of extensions: Querytotextbyxfdtshowknn. Factor: Minwindowsize by Stream Body. The total balanced values ​​of the factor multiplied by weight (\ frac {\ sum w_i * (w_i * f_i)} {\ sum w_i}) normalized for total weight.

Linguistic boosting factor. Type of extensions: Querytotextbyxfdtshowknn. Factor: Norm256 by stream BOCM11. The total balanced values ​​of the factor multiplied by weight (\ frac {\ sum w_i * (w_i * f_i)} {\ sum w_i}) according to the expansion top.

Linguistic boosting factor. Type of extensions: Querytotextbyxfdtshowknn. The minimum expansion weight.

Linguistic boosting factor. Type of extensions: Querytotextbyxfdtshowknn. The arithmetic mean of expansion weights.

Linguistic boosting factor. Type of extensions: Querytotextbyxfdtshowknn. The total weight of the extensions.

Linguistic boosting factor. Type of extensions: Querytotextbyxfdtshowknn. Factor: ORIGINALREQUENTFRACTFRACTION OF THE FIELDSETBAGOFWORDS Stream.

Characterizes the request for the degree of change from the addition of a fixed word (number of some year), DSSM model DSSMBOOSTINGXFONESEAMSARD is used

Characterizes a request for the degree of change from the addition of a fixed word ('online' for Kirilitsa), DSSM model DSSMBOOSTINGXFONESEAMSARD is used

Characterizes the request for the degree of change from removing a fixed word ('site' for Kirilitsa), DSSM model DSSMBOOSTINGXFONESEAMSARD is used

The initial request with the removal of verbs. It is considered according to the heading of the document. The algorithm for aggregation of the scales of words: BM15. Normalization coefficient 0.1.

The initial request with the removal of verbs. It is considered to be composational stream, consisting of an tokenized Url and a title of a document. The algorithm for aggregation of the scales of words: BM15FLOGW0. Normalization coefficient 0.0001.

The initial request with the removal of verbs. It is considered according to the contents of the document. The minimum window size, which includes all the words of the request. It is normalized for the number of words in the request.

The initial request with the removal of verbs. It is considered to be toxicated by Ural. The algorithm for aggregation of the scales of words: BM15. Normalization coefficient 0.1.

The result of the use of a neural model, trained to distinguish long clicks from other events, the input of the model is the ambassadors and bigram meters, calculated by text streams (Title, Body, URL).

The factor for the filtered original request: the DSSM state from the request is calculated without words to the initial request, after which the threshold is cut off. Into aircraft association of the URLs, Title, Body, Links, Correctedctr, LongClick, OneClick, Browserpagerank, Splitdwelltime, SampleperiodDayFrc, SimpleClick, Yabarvisits, Yabartime. The algorithm for aggregation of the scales of words: BM15FLOG (BM15 Aggregation of Logarithm of Construction of Words). Normalization coefficient 0.001.

The factor for the filtered original request: the DSSM state from the request is calculated without words to the initial request, after which the threshold is cut off. It is considered to be composational stream, consisting of an tokenized Url and a title of a document. The algorithm for aggregation of the scales of words: BM15FLOGW0. Normalization coefficient 0.0001.

For all words of the request, the weight is calculated by the Query-Mutation method (the distance between the requests in nash and there is no word). The sum of the scales of the words found in the title is taken, divided by the sum of the scales of all words.

For all words of the request, the weight is calculated by the Query-Mutation method (the distance between the requests in nash and there is no word). Maximum weight is taken among words absent in the title of the document.

The result of the use of a neural model, trained to distinguish long clicks from other events, the input of the model is the ambassadors and bigram meters calculated by text streams (Body, URL).

The request was recognized as having intent to copyright objects protected by anti-Pirate memorandum.

Transferred Ethos predicted classifier for marking on the relevance of video.

Reduced ETHOS predictive classifier, trained in the synthetic sample 'Request characteristic of the pirate site' VS 'Request is characteristic of the site far from this'

DSSM regression for the separation of memorandum and no requests

Transferred Ethos predicted classifier trained to distinguish a memorandum queries from a random

DSSM regression of embeds to separate Pirato specific and no requests

Characterizes the request for the degree of change from removing a fixed word ('site' for Kirilitsa), DSSM model DSSMBOOSTINGXFONESEAMSARD is used

Characterizes the request for the degree of change from the addition of a fixed word (number of some year), DSSM model DSSMBOOSTINGXFONESEAMSARD is used

Characterizes a request for the degree of change from the addition of a fixed word ('online' for Kirilitsa), DSSM model DSSMBOOSTINGXFONESEAMSARD is used

The request was recognized as having intent to copyright objects protected by anti-Pirate memorandum.

Transferred Ethos predicted classifier for marking on the relevance of video.

Reduced ETHOS predictive classifier, trained in a synthetic sample 'Request characteristic of the pirate site' VS ', the request is characteristic of the site far from this'

DSSM regression for the separation of memorandum and no requests

Transferred Ethos predicted classifier trained to distinguish a memorandum queries from a random

DSSM regression of embeds to separate Pirato specific and no requests

The query getting into the TOP 11 clusters on Kernel metric based on DSSM proximity.

Requests got into the 34th cluster based on CTR-DSSM.

Constant 1

1/(1 + number of words of the request), attributes are not taken into account

Is an attribute request (looks at rearr = attrs)

Median dwelltai request in history. Dwelltaym is cut to 6000. The request is normalized by doppelgangers

Characterizes the request for the degree of change from the addition of a fixed word (number of some year), DSSM model DSSMBOOSTINGXFONESEAMSARD is used

Characterizes the request for the degree of change from removing a fixed word ('site' for Kirilitsa), DSSM model DSSMBOOSTINGXFONESEAMSARD is used

Characterizes the request for the degree of change from the addition of a fixed word (number of some year), DSSM model DSSMBOOSTINGXFONESEAMSARD is used

Characterizes a request for the degree of change from the addition of a fixed word ('online' for Kirilitsa), DSSM model DSSMBOOSTINGXFONESEAMSARD is used

FIO Wizard FIO Wizard

Characterizes the request for the degree of change from the addition of a fixed word (number of some year), DSSM model DSSMBOOSTINGXFONESEAMSARD is used

Factor about the presence of a symbol '?' In Url. It is zero if the Url has CGI parameters (more precisely: all duplicate have a symbol '?' In Url).

Equal to one if the page connects JS-API of any geo-data supplier

The request was recognized as having intent to copyright objects protected by anti-Pirate memorandum.

Characterizes the request for the degree of change from the addition of a fixed word (number of some year), DSSM model DSSMBOOSTINGXFONESEAMSARD is used

It characterizes the request for the degree of change from the addition of a fixed word ('online' for Kirilitsa), the DSSM model DSSMBOOSTINGXFONESEAMSHARD is used. It is also used in the ranking of ether.

Characterizes the request for the degree of change from removing a fixed word ('site' for Kirilitsa), DSSM model DSSMBOOSTINGXFONESEAMSARD is used

The factor about the presence of a symbol '? ' In Url. It is zero if the Url has CGI parameters (more precisely: all duplicate have a symbol '? ' In Url).

Equal to one if the page connects JS-API of any geo-data supplier

The factor about the presence of a symbol '? ' In Url. It is zero if the Url has CGI parameters (more precisely: all duplicate have a symbol '? ' In Url).

Equal to one if the page connects JS-API of any geo-data supplier

Linguistic boosting factor. Type of extensions: QFUF. Aggregation on all extensions. The amount by the square of the expansion, multiplied by the value of the factor. Normalized for the total weight of extensions. Compositional TR-Like stream, which includes URL, headline, and the body of the document. PerwordCmmaxMatchMin algorithm: At least according to the maximum of the CMMAXMATCH weight abstracts.

Linguistic boosting factor. Type of extensions: QFUF. Aggregation on all extensions. The greatest value of the factor. Compositional TR-Like stream, which includes URL, headline, and the body of the document. Algorithm for aggregation of the scales of words BOCM15. Normalization coefficient 0.01.

Linguistic boosting factor. Type of extensions: QFUF. Aggregation on all extensions. The greatest value of the factor. Compositional TR-Like stream, which includes URL, headline, and the body of the document. Word Libra aggregation algorithm: BCLMWEIDEDPROXIMITY1BM15SIZE1. Normalization coefficient 0.001.

Linguistic boosting factor. Type of extensions: QFUF. Aggregation on all extensions. The greatest value of the factor. Compositional TR-Like stream, which includes URL, headline, and the body of the document. The algorithm for aggregation of the scales of words: bclmlite, adaptation of the corresponding TR factor.

Linguistic boosting factor. Type of extensions: QFUF. Aggregation on all extensions. The greatest balanced value of the factor. Normalized for the total weight of extensions. Compositional TR-Like stream, which includes URL, headline, and the body of the document. The sum of the scales of words, balanced by the weight of the annotation, is normalized for the sum of the scales of words. Only annotations are calculated, on which the sum of words of words is more than 80%.

Linguistic boosting factor. Type of extensions: QFUF. Aggregation by TOP-10 (by the value of the factor) extensions. A suspended sum of the Libra of factors. Normalized for the total weight of extensions. Compositional TR-Like stream, which includes URL, headline, and the body of the document. Algorithm for aggregation of the scales of words BOCM15. Normalization coefficient 0.01.

Linguistic boosting factor. Type of extensions: QFUF. Aggregation on all extensions. The amount by the square of the expansion, multiplied by the value of the factor. Normalized for the total weight of extensions. Compositional TR-Like stream, which includes URL, headline, and the body of the document. The algorithm for aggregation of the scales of words: bclmlite, adaptation of the corresponding TR factor.

Linguistic boosting factor. Type of extensions: QFUF. Aggregation on all extensions. A suspended sum of the Libra of factors. Normalized for the total weight of extensions. Compositional TR-Like stream, which includes URL, headline, and the body of the document. PerwordCmmaxMatchMin algorithm: At least according to the maximum of the CMMAXMATCH weight abstracts.

DSSM model of panther terms. Embed -expanded bar are used for L2. Top5 QFUF of Cosine proximity to the Embed document is filtered. As a factor, a minimum of the weight of the expansion of proximity is used.

DSSM model of panther terms. Embed -expanded bar are used for L2. Top5 QFUF of Cosine proximity to the Embed document is filtered. Next, the weighed amount of proximity is calculated, the weight of the expansion is used in the quality of weight, normalized for the amount of the weights of filtered extensions.

DSSM model of panther terms. Embed -expanded bar are used for L2. As a factor, the average proximity to the Embed of the document is used.

DSSM model of panther terms. Embed -expanded bar are used for L2. As a factor, a minimum of the weight of the expansion of proximity is used.

The factor for telephone attributes Tel_Full from the original request text of the document. Algorithm for aggregation of the scales of words BOCM15. Normalization coefficient 0.01.

not used

not used

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not used

The average value of the QFUFTOPSUMWFSUMWFELDSET3BCLMWEIGHTEDFLOGW0K0001 factor is average according to documents with video

The medium -enactable value of the QFUFTOPSUMWFSUMWFELDSET3BCLMWEIGHTEDFLOGW0K0001 factor, the PRS documents from PRS - HostStevensonweight

sbr:2411087272 splitv3 head Predict_jul_xlarge_lav_with_platform_2344793612_stand_mse

sbr:2411087272 splitv3 head Predict_jul_xlarge_sinsig_baskets_with_platform_2339818891_stand_mse

berts_storage:2022/02/artmironov/2831823537 splitv4 head Predict_bert_650_merge_platform_no_trans_v1_2784077050_stand_mse

empty slot

empty slot

empty slot

bert model 2021/09/boyalex/2405042847 head: Predict_jul_xlarge_sinsig_baskets_2339818891_stand_mse

bert model 2021/09/boyalex/2405042847 head: Predict_large_cs_clever_clicks_2360931838_stand_mse

bert model 2021/09/boyalex/2405042847 head: Predict_large_google_2334139725_stand_mse

bert model 2021/09/boyalex/2405042847 head: Predict_pq_large_2394064809_stand_mse

bert model 2021/09/boyalex/2405042847 head: Predict_jul_xlarge_cs_sinsig_full_2394990987_stand_mse

bert model 2021/09/boyalex/2405042847 head: Predict_jul_xlarge_cs_apscore_2397363137_stand_mse

Characterizes the request for the degree of change from removing a fixed word ('site' for Kirilitsa), DSSM model DSSMBOOSTINGXFONESEAMSARD is used

Characterizes the request for the degree of change from the addition of a fixed word (number of some year), DSSM model DSSMBOOSTINGXFONESEAMSARD is used

Characterizes a request for the degree of change from the addition of a fixed word ('online' for Kirilitsa), DSSM model DSSMBOOSTINGXFONESEAMSARD is used

Text Machine AnnotationMaxValueWeighted feature on all panther match without panther relevance

Text Machine CosineMatchMaxPrediction feature on all panther match without panther relevance

Text Machine Bm15_K0.1 feature on all panther match without panther relevance

Text Machine WordCoverageAny feature on all panther match without panther relevance

Text Machine AnnotationMaxValueWeighted feature on panther match relevance

Text Machine CosineMatchMaxPrediction feature on panther match relevance

Text Machine Bm15_K0.1 feature on panther match relevance

Text Machine WordCoverageAny feature on panther match relevance

Text Machine AnnotationMaxValueWeighted feature on panther match without relevance

Text Machine CosineMatchMaxPrediction feature on panther match without relevance

Text Machine Bm15_K0.1 feature on panther match without relevance

Text Machine WordCoverageAny feature on panther match without relevance

Text Machine AnnotationMaxValueWeighted feature on panther match

Text Machine CosineMatchMaxPrediction feature on panther match

Text Machine Bm15_K0.1 feature on panther match

Text Machine WordCoverageAny feature on panther match

Text Machine AnnotationMaxValueWeighted feature on panther match

Text Machine CosineMatchMaxPrediction feature on panther match

Text Machine Bm15_K0.1 feature on panther match

Text Machine WordCoverageAny feature on panther match

Text Machine AnnotationMaxValueWeighted feature on panther match

Text Machine CosineMatchMaxPrediction feature on panther match

Text Machine Bm15_K0.1 feature on panther match

Text Machine WordCoverageAny feature on panther match

user-bert-model sbr:2366952047 predict, distilled small pers model predicts

user-bert-model sbr:2366952047 predict, distilled small odd model predict

user-bert-model sbr:2366952047 predict, distilled small surplus model predict

user-bert-model sbr:2366952047 predict, distilled small lintr model predict

user-bert-model sbr:2366952047 predict, distilled small pos1 model predict

user-bert-model sbr:2366952047 predict, distilled small pos4 model predict

Features personal model pers predict

Features personal model odd predict

Features personal model tr predict

Features personal model surplus predict

Features personal model surplus predict

Features personal model surplus predict

Features personal model surplus predict