Abstract:The objective of this study was to describe the criteria mentioned by users evaluating the information within documents as it related to the users' information need situations. Data were collected by asking users in an academic environment to evaiu-ate representations and the full text of documents that had been retrieved specifically for each user's information need situation. Users were asked to mark the portions of the document representations or of the full text of documents that indicated to the users whe… Show more
“…Research into the concept of relevance has indicated that topicality plays a significant role in the determination of relevance, although it does not automatically result in relevance for users (Barry, 1994).…”
Abstract. The application of document clustering to information retrieval has been motivated by the potential effectiveness gains postulated by the cluster hypothesis. The hypothesis states that relevant documents tend to be highly similar to each other, and therefore tend to appear in the same clusters. In this paper we propose an axiomatic view of the hypothesis, by suggesting that documents relevant to the same query (co-relevant documents) display an inherent similarity to each other which is dictated by the query itself. Because of this inherent similarity, the cluster hypothesis should be valid for any document collection. Our research describes an attempt to devise means by which this similarity can be detected. We propose the use of query-sensitive similarity measures that bias interdocument relationships towards pairs of documents that jointly possess attributes that are expressed in a query. We experimentally tested three query-sensitive measures against conventional ones that do not take the context of the query into account, and we also examined the comparative effectiveness of the three query-sensitive measures. We calculated interdocument relationships for varying numbers of top-ranked documents for six document collections. Our results show a consistent and significant increase in the number of relevant documents that become nearest neighbours of any given relevant document when query-sensitive measures are used. These results suggest that the effectiveness of a cluster-based IR system has the potential to increase through the use of query-sensitive similarity measures.
“…Research into the concept of relevance has indicated that topicality plays a significant role in the determination of relevance, although it does not automatically result in relevance for users (Barry, 1994).…”
Abstract. The application of document clustering to information retrieval has been motivated by the potential effectiveness gains postulated by the cluster hypothesis. The hypothesis states that relevant documents tend to be highly similar to each other, and therefore tend to appear in the same clusters. In this paper we propose an axiomatic view of the hypothesis, by suggesting that documents relevant to the same query (co-relevant documents) display an inherent similarity to each other which is dictated by the query itself. Because of this inherent similarity, the cluster hypothesis should be valid for any document collection. Our research describes an attempt to devise means by which this similarity can be detected. We propose the use of query-sensitive similarity measures that bias interdocument relationships towards pairs of documents that jointly possess attributes that are expressed in a query. We experimentally tested three query-sensitive measures against conventional ones that do not take the context of the query into account, and we also examined the comparative effectiveness of the three query-sensitive measures. We calculated interdocument relationships for varying numbers of top-ranked documents for six document collections. Our results show a consistent and significant increase in the number of relevant documents that become nearest neighbours of any given relevant document when query-sensitive measures are used. These results suggest that the effectiveness of a cluster-based IR system has the potential to increase through the use of query-sensitive similarity measures.
“…), publishing date (e.g., year), and its text. These attributes can contain specific words, i.e., terms that can be recognized by the information seeker as relevant and trigger the formulation of refined search queries (Barry, 1994;Anderson, 2006).…”
Abstract:This paper presents preliminary results of our current research project DiLiA (Digital Library Assistant).The goals of the project are are twofold. One goal of the project is the development of domain-independent information extraction methods. The other goal is the development of information visualization methods that interactively support researchers at time consuming information discovery tasks. We first describe issues that contribute to high cognitive load during exploration of unfamiliar research domains. Then we present a domain-independent approach to technical term extraction from paper abstracts, describe the architecture of the DiLiA, and illustrate an example co-author network visualization.
“…They found that typicality, emotion and aesthetic appearance were the three most important criteria, applied across all three tasks, where typicality was deemed the most important criterion for all three tasks (according to the authors, typicality is a criterion that can exhibit universal representation of an object in a photo). Lancaster (1979); Barry (1994); Barry and Schamber (1998);Mizzaro (1997); Choi and Rasmussen (2002) and Tang and Solomon (1998) reported that the end-users of IR systems decided the relevance of retrieved documents based upon their particular information needs.…”
This paper reports the results of a study investigating the relevance criteria used by health care professionals when seeking medical images. Data was collected from 26 participants using a think-a-loud protocol and face-to-face interviews and analysed using the Straussian version of Grounded Theory (GT). Findings show that participants made use of 27 relevance criteria, although did not agree on the most important. Our findings suggest that users apply different criteria in different situations when evaluating the relevancy of medical images. In addition, we have investigated the coverage of relevance criteria to search statements from the medical track of ImageCLEF (ImageCLEFMed). Analysis indicates that some of the criteria identified by our participants could be included in future runs of the international evaluation campaign.
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