| A recall in information retrieval is searching for | | | | non-relevant documents. |
| information in documents in connection with the | | | | Many use the IR Systems such as: |
| query. | | | | - universities |
| The word RECALL pertains to: | | | | - public libraries |
| - Product Recall | | | | - web |
| - Recall Election | | | | There are proposals of different measures so as to |
| - Letter to Recall | | | | evaluate information retrieval systems. It requires a |
| - Recall to Employment | | | | collection of documents and a query. All measures |
| - Recall from Memory | | | | assume the truth concept of relevancy. It may be |
| - Recall (Information Retrieval) | | | | known either as non-relevant or relevant to the |
| - Recall (Bugle call) | | | | query. Queries may be ill-posed. There may be |
| - Recall (Broadcasting) | | | | different shades of relatedness. |
| - Recall (Email) | | | | The portion of the documents retrieved which are |
| Information Retrieval also is the science of searching | | | | related to the user's information need is called |
| for the following: | | | | PRECISION. |
| - documents | | | | Precision is similar to the positive predictive value |
| - information within documents and | | | | within a binary classification. Precision takes all the |
| - for metadata about documents | | | | retrieved documents. It can be assessed at a |
| - as well as that of searching relational data bases | | | | specified cut-off rank. It needs to consider only the |
| and the | | | | top results returned by the system. This measure is |
| - world wide web | | | | called precision at n or P@n. Precision in Information |
| Information Retrieval is Interdisciplinary. It is based on: | | | | Retrieval is different from accuracy and precision of |
| - Computer Science | | | | other branches of science and technology. |
| - Mathematics | | | | A Fall-out is closely related to "specificity" in a binary |
| - Library Science | | | | classification. |
| - Information Science | | | | To be exact: fall-out is equal to 1 minus specificity. |
| - Information Architecture | | | | It is the chance that a non-relevant document can be |
| - Cognitive Psychology | | | | retrieved by the query. It is insignificant to achieve |
| - Linguistics | | | | fall-out of 0%. It is also done by returning zero |
| - Statistics and | | | | documents in response to any query. |
| - Physics | | | | The F1 measure is the weighed harmonic means of |
| When a user enters a query into the system, it is | | | | precision and recall. It is the conventional F-measure |
| then considered as the beginning of information | | | | or balanced F-score. |
| retrieval process. | | | | Two other commonly used F measures are: |
| WHAT ARE QUERIES? | | | | 1. F2 measure - weighs recall twice as much as |
| Queries are official statements of information needed | | | | precision |
| in information retrieval. Through this, a query does | | | | 2. F0.5 measure - weighs precision twice as much as |
| not identify, individually, a single object in the group. | | | | recall. |
| As a substitute, numerous objects may match the | | | | Van Rijsbergen derived the F-measure. It is to |
| query. It can also match different degrees of | | | | measure Fβ's effectiveness on retrieval in |
| relevancy. | | | | connection with a user who assigns β |
| A certain object is a unit which stores information in | | | | times as much weight to retrieve as precision. |
| a database. The user's queries are then matched with | | | | It relies on the effectiveness measure of |
| objects so as to keep it in the database. Usually, the | | | | Rijsbergen's: |
| documents are not stored directly in the IR System. | | | | E = 1 - (1/(a/P + (1 - a) / R )). |
| Document surrogate is the name of the | | | | Their relationship stands as Fβ = 1 - E |
| representation of the system. | | | | Where in: α = 1 / (β2 + 1) |
| Many IR systems use a numeric score so as to | | | | The basis of precision and recall are on the complete |
| compute how well each object matches the query. It | | | | records of document returned by the system. The |
| ranks the objects according to this value. The top | | | | normal precision emphasizes on returning more |
| ranking object will then be apparent. It may then be | | | | related documents earlier. It is average precision that |
| iterated if you want to refine the query. | | | | is computed after truncating the list and following the |
| Recall is the sensitivity in a binary arrangement. There | | | | related documents which in turn: |
| is a chance that a relevant document can be | | | | Where:r indicates the rank |
| retrieved by the query. | | | | N indicates the number recalledrel() indicates a binary |
| To answer any query, it is insignificant to achieve a | | | | function regarding the importance of a specified rank, |
| recall of 100%. It means the recall alone is not | | | | and |
| enough. It also needs to measure the number of | | | | P() indicates precision at a specified cut-off rank. |