public class NetricsSearchResult extends NetricsMappedRecord implements java.io.Serializable
NetricsRecord.ChildType| Modifier and Type | Method and Description |
|---|---|
int[] |
getCharMatchStrengths(int fieldNo)
Returns the match strength information for a searchable-text
field in the record.
|
int[] |
getCharMatchStrengths(java.lang.String fieldName)
Returns the match strength information for a searchable-text
field in the record.
|
double[] |
getDblCharMatchStrengths(int fieldNo)
Returns the precomputed visualization strengths for a
searchable-text field.
|
double[] |
getDblCharMatchStrengths(java.lang.String fieldName)
Returns the precomputed visualization strengths for a
searchable-text field.
|
boolean |
getDirtyState()
The dirty state for this record.
|
java.lang.String |
getHtml(int fieldNo)
Gets an HTML visualized field from the record.
|
java.lang.String |
getHtml(java.lang.String fieldName)
Gets an HTML visualized field from the record.
|
double |
getITMatchScore()
A score from 0 to 1.0 indicating the information theoretic
score for this record.
|
double[] |
getITMatchScoreQlt()
The per-querylet IT match scores.
|
int |
getMatchRank()
The ordinal ranking of this record.
|
double |
getMatchScore()
The score that was used to sort the record.
|
double[] |
getMatchScoreQlt()
Querylet match scores.
|
java.lang.String |
getMatchType()
The type of search which retrieved this record.
|
double |
getMaxMatchScore()
A score from 0 to 1.0 indicating the maximum of the normal
and reverse match strengths for this record.
|
double |
getMinMatchScore()
A score from 0 to 1.0 indicating the minimum of the normal
and reverse match strengths for this record.
|
double |
getNamedQltConfidence(java.lang.String qlet_name)
Get the confidence measure of the named querylet.
|
double[] |
getNamedQltConfidenceArray()
Get the list of named querylet confidence measures, null if none.
|
java.lang.String[] |
getNamedQlts()
Get the list of named querylets, null if none.
|
double |
getNamedQltScore(java.lang.String qlet_name)
Get the match score of the named querylet.
|
double[] |
getNamedQltScoresArray()
Get the list of named querylet scores, null if none.
|
double |
getNormMatchScore()
A score from 0 to 1.0 indicating the normal match strength for this
record.
|
double[] |
getNormMatchScoreQlt()
The per-querylet normal match scores.
|
double |
getRevMatchScore()
A score from 0 to 1.0 indicating the reverse match
strength for this record.
|
double[] |
getRevMatchScoreQlt()
The per-querylet reverse match scores.
|
double |
getRlConfidence()
Get the Learn Model (RLINK) confidence measure.
|
double |
getRlScore()
Deprecated.
use
getMatchScore() to get the Learn model score for RLink queries. |
double[] |
getRlSignificances()
Get the Learn Model (RLINK) significance values.
|
java.lang.String |
getSrcDbInfo()
Deprecated.
use
getSrcTblInfo() |
java.lang.String |
getSrcDbName()
Deprecated.
use
getSrcTblName() |
java.lang.String |
getSrcTblInfo()
The table info field for the table from which the record came.
|
java.lang.String |
getSrcTblName()
The name of the table from which the record came.
|
double |
getSymMatchScore()
A score from 0 to 1.0 indicating the symmetric match
strength for this record.
|
double[] |
getSymMatchScoreQlt()
The per-querylet symmetric match scores.
|
getAttribute, getAttrNames, getField, getField, getFieldNames, getFieldTypes, toStringcompare, getAttribute, getAttrNames, getAttrValues, getFields, getKey, getParentKey, numBytespublic int[] getCharMatchStrengths(java.lang.String fieldName)
throws NetricsException
The core search algorithm creates match strengths for each character in a matching record. These strengths are represented as an integer where 0 indicates no match and higher numbers represent a better match.
fieldName - The name of the field for which to return its match
strength information.NetricsException - if the field name is invalid.public int[] getCharMatchStrengths(int fieldNo)
fieldNo - The number of the field for which to return its
match strength information.public double[] getDblCharMatchStrengths(java.lang.String fieldName)
throws NetricsException
These are per character match quality score values where 0.0 represents no match and 1.0 represents a perfect match. These scores account for more factors than the integer match scores and are the preferred character strength scores to use.
fieldName - The name of the field for which to return its
match strength information.NetricsException - if the field name is not in the results.public double[] getDblCharMatchStrengths(int fieldNo)
These are per character match quality score values where 0.0 represents no match and 1.0 represents a perfect match. These scores account for more factors than the integer match scores and are the preferred character strength scores to use.
fieldNo - The number of the field for which to return its
match strength information.public java.lang.String getHtml(java.lang.String fieldName)
throws NetricsException
Gets the content of a given field with matching characters visualized using HTML. Parameters for the visualization can be set in the NetricsSearchOpts object.
fieldName - The name of the field for which to get the HTML visualized string.NetricsException - if the field name is not in the results.NetricsSearchOptspublic java.lang.String getHtml(int fieldNo)
Gets the content of a given field with matching characters visualized using HTML. Parameters for the visualization can be set in the NetricsSearchOpts object.
fieldNo - The index of the field for which to get the HTML visualized string.NetricsSearchOptspublic double getMatchScore()
NetricsQuery.scoreType(int)public double getNormMatchScore()
NetricsQuery.scoreType(int)public double getRevMatchScore()
NetricsQuery.scoreType(int)public double getSymMatchScore()
NetricsQuery.scoreType(int)public double getMinMatchScore()
NetricsQuery.scoreType(int)public double getMaxMatchScore()
NetricsQuery.scoreType(int)@Deprecated public double getRlScore()
getMatchScore() to get the Learn model score for RLink queries.public double getITMatchScore()
public double[] getMatchScoreQlt()
If the top level query is a score combiner these are the match scores of the individual querylets of the score combiner. E.g. if you have a simple query for each field in the record combined with an AND these would be the scores of the simple queries, and thus the scores for the individual fields.
NetricsQuery.scoreType(int)public double[] getNormMatchScoreQlt()
NetricsQuery.scoreType(int)public double[] getRevMatchScoreQlt()
NetricsQuery.scoreType(int)public double[] getSymMatchScoreQlt()
NetricsQuery.scoreType(int)public double[] getITMatchScoreQlt()
NetricsQuery.scoreType(int)public double[] getRlSignificances()
This returns the significance array for RLINK queries. If the top level query was not an RLINK query null is returned. If this result does not represent what the Learn Model considers a match, null is returned.
There is one significance value for each querylet input to the RLINK query. Note this is not per record field, it is per input querylet. Each entry is a value between 0.0 and 1.0. The value defines the relative importance of each querylet in determining this was a match. Querylets with high significance scores were considered relevant in making the decision, querylets with low scores were not relevant. The scores are proportional values and not based on an absolute scale.
public double getRlConfidence()
Only Rlink queries produce a confidence value other than 1.0. However confidence values are passed up, so score combiners may return a confidence value from a lower level Rlink query.
The calculation of a confidence measure by an Rlink query can be turned off. When confidence calculation is turned off the special value: -999.0 is produced.
The confidence measure is a value between 0.0 and 1.0. It gives an estimate of how confident the model is in the prediction it made. This is based primarily on how well trained the model is for the this particular match case. A value of 0.0 indicates no confidence at all in the prediction, i.e. the model was not trained in this case or the training was very contradictory, so the model is only estimating the score. A value of 1.0 means complete confidence. The dividing line between good confidence values and bad ones depends on the application and the confidence measure used.
public java.lang.String[] getNamedQlts()
public double[] getNamedQltScoresArray()
public double getNamedQltScore(java.lang.String qlet_name)
throws NetricsException
qlet_name - the name of the querylet.NetricsException - if qlet_name is null or there is
no querylet with the given name.public double[] getNamedQltConfidenceArray()
public double getNamedQltConfidence(java.lang.String qlet_name)
throws NetricsException
qlet_name - the name of the querylet.NetricsException - if qlet_name is null or there is
no querylet with the given name.public java.lang.String getSrcTblName()
public java.lang.String getSrcDbName()
getSrcTblName()public java.lang.String getSrcTblInfo()
public java.lang.String getSrcDbInfo()
getSrcTblInfo()public java.lang.String getMatchType()
public int getMatchRank()
public boolean getDirtyState()