Term Proximity Scoring for Keyword-Based Retrieval Systems

Abstract

Abstract. This paper suggests the use of proximity measurement in combination with the Okapi probabilistic model. First, using the Okapi system, our investigation was carried out in a distributed retrieval framework to calculate the same relevance score as that achieved by a single centralized index. Second, by applying a term-proximity scoring heuristic to the top documents returned by a keyword-based system, our aim is to enhance retrieval performance. Our experiments were conducted using the TREC8, TREC9 and TREC10 test collections, and show that the suggested approach is stable and generally tends to improve retrieval effectiveness especially at the top documents retrieved.

Arabic Document Classification Using Multiword Features

“…For example, they have been embodied in document ranking, passage retrieval and other information retrieval models [4], [18]. Nevertheless, Tao and Zhai [22] indicate that the use of Arabic Document Classification Using Multiword Features Diab Abuaiadah proximity and multiword features in information retrieval is underexplored.…”

“…In this method the input document is converted to a bag-of-words where the frequencies of terms are considered and the relative positions of terms in the text are ignored. This dramatically simplifies the computational complexities of the accompanying algorithms and is widely used by researchers at academic institutions and incorporated in several industry products [4], [18], [19], [20].…”

A 3-tuple information retrieval query interface with ontology based ranking

“…[4,5,6]. Among them, for multikeyword search, the most important factors to determine their ranking results are frequency and proximity [4,6,7,8,9,10,11,12]. One of the main problems with the current ranking algorithm of multi-word search arises from the fact that its methodology calculates the relevance of keywords only by their proximity without considering whether they exist in the same sentence or not.…”

“…As several researches on proximity search show [6,7,8,9,10,11,12], this method has improved information retrieval a great deal. To calculate proximity, the proximity search considers distance between keywords.…”

Sentence-based relevance flow analysis for high accuracy retrieval

“…Some work tried to integrate proximity features into bag-of-words ranking models. Rasolofo and Savoy (2003) added proximity information to the Okapi probabilistic model and found improved performance specifically among the top scored documents. Buttcher, Clarke, and Lushman (2006) also incorporated proximity into the Okapi BM25 model and observed positive results.…”