Distance Measures¤
Distance Measures compute a distance metric between two sets of strings.
Intended audience: Linked Data Experts and Domain Experts
| Name | Description |
|---|---|
| CJK reading distance | CJK Reading Distance. |
| Compare physical quantities | Computes the distance between two physical quantities. |
| Constant similarity value | Always returns a constant similarity value. |
| Cosine | Cosine Distance Measure. |
| Date | The distance in days between two dates (‘YYYY-MM-DD’ format). |
| DateTime | Distance between two date time values (xsd:dateTime format) in seconds. |
| Dice coefficient | Dice similarity coefficient. |
| Geographical distance | Computes the geographical distance between two points. Author: Konrad Höffner (MOLE subgroup of Research Group AKSW, University of Leipzig) |
| Greater than | Checks if the source value is greater than the target value. If both strings are numbers, numerical order is used for comparison. Otherwise, alphanumerical order is used. |
| Inequality | Returns success if values are not equal, failure otherwise. |
| Inside numeric interval | Checks if a number is contained inside a numeric interval, such as ‘1900 - 2000’. |
| Is substring | Checks if a source value is a substring of a target value. |
| Jaccard | Jaccard similarity coefficient. Divides the matching tokens by the number of distinct tokens from both inputs. |
| Jaro distance | Matches strings based on the Jaro distance metric. |
| Jaro-Winkler distance | Matches strings based on the Jaro-Winkler distance measure. |
| Korean phoneme distance | Korean phoneme distance. |
| Korean translit distance | Transliterated Korean distance. |
| Levenshtein distance | Levenshtein distance. Returns a distance value between zero and the size of the string. |
| Lower than | Checks if the source value is lower than the target value. |
| Normalized Levenshtein distance | Normalized Levenshtein distance. Divides the edit distance by the length of the longer string. |
| Numeric equality | Compares values numerically instead of their string representation as the ‘String Equality’ operator does. Allows to set the needed precision of the comparison. A value of 0.0 means that the values must represent exactly the same (floating point) value, values higher than that allow for a margin of tolerance. |
| Numeric similarity | Computes the numeric distance between two numbers. |
| qGrams | String similarity based on q-grams (by default q=2). |
| Relaxed equality | Return success if strings are equal, failure otherwise. Lower/upper case and differences like ö/o, n/ñ, c/ç etc. are treated as equal. |
| Soft Jaccard | Soft Jaccard similarity coefficient. Same as Jaccard distance but values within an levenhstein distance of ‘maxDistance’ are considered equivalent. |
| Starts with | Returns success if the first string starts with the second string, failure otherwise. |
| String equality | Checks for equality of the string representation of the given values. Returns success if string values are equal, failure otherwise. For a numeric comparison of values use the ‘Numeric Equality’ comparator. |
| Substring comparison | Return 0 to 1 for strong similarity to weak similarity. Based on the paper: Stoilos, Giorgos, Giorgos Stamou, and Stefanos Kollias. “A string metric for ontology alignment.” The Semantic Web-ISWC 2005. Springer Berlin Heidelberg, 2005. 624-637. |
| Token-wise distance | Token-wise string distance using the specified metric. |