Application of aboutness to functional benchmarking in information retrieval

Experimental approaches are widely employed to benchmark the performance of an information retrieval (IR) system. Measurements in terms of recall and precision are computed as performance indicators. Although they are good at assessing the retrieval effectiveness of an IR system, they fail to explore deeper aspects such as its underlying functionality and explain why the system shows such performance. Recently, inductive (i.e., theoretical) evaluation of IR systems has been proposed to circumvent the controversies of the experimental methods. Several studies have adopted the inductive approach, but they mostly focus on theoretical modeling of IR properties by using some metalogic. In this article, we propose to use inductive evaluation for functional benchmarking of IR models as a complement of the traditional experiment-based performance benchmarking. We define a functional benchmark suite in two stages: the evaluation criteria based on the notion of "aboutness," and the formal evaluation methodology using the criteria. The proposed benchmark has been successfully applied to evaluate various well-known classical and logic-based IR models. The functional benchmarking results allow us to compare and analyze the functionality of the different IR models

On the Accuracy of Hyper-local Geotagging of Social Media Content

Social media users share billions of items per year, only a small fraction of which is geotagged. We present a data- driven approach for identifying non-geotagged content items that can be associated with a hyper-local geographic area by modeling the location distributions of hyper-local n-grams that appear in the text. We explore the trade-off between accuracy, precision and coverage of this method. Further, we explore differences across content received from multiple platforms and devices, and show, for example, that content shared via different sources and applications produces significantly different geographic distributions, and that it is best to model and predict location for items according to their source. Our findings show the potential and the bounds of a data-driven approach to geotag short social media texts, and offer implications for all applications that use data-driven approaches to locate content.Comment: 10 page

Case Grammar And Functional Relations In Aboutness Recognition And Relevance Decision-making In The Bibliographic Retrieval Environment

One of the most perplexing problems in Information Science has been definition of central concepts such as \u27relevance\u27 and \u27information\u27 at a theoretical level which incorporates and accounts for all known attributes of the concepts and the principles which underlie their particular application in this field. The objective of this thesis was to determine whether one definition of relevance, \u27aboutness\u27, can be based, at least in part, on textual characteristics of queries and abstracts. To this end, this study was conducted to determine to what extent a set of functional relations based on Fillmore\u27s case grammar theory could be used to explain the correspondence between patterns of language behavior in aboutness recognition and language patterns in the texts of queries and abstracts. The test environment was a real-life bibliographic retrieval system. Thirty subject specialists (advanced graduate students and university faculty from the Sciences, Social Sciences and Humanities) submitted queries and performed relevance assessments using \u27aboutness\u27 as the operational definition for their judgements. An analysis of functional relations between the keyterms in the queries and abstracts was compared to the subject specialists\u27 decisions. The result was that the agreement between the subject specialists\u27 decisions and the decisions based on a match in functional relations between the queries and abstracts was 97%. The conclusion reached on the basis of this finding is that abstracts judged to be about the topic named in a query did contain the desired keyterms in functional relations which matched the functional relations between those keyterms in the query; and abstracts judged to be not about the topic named in the query did contain the same or equivalent keyterms, but not in functional relations which matched the functional relations in the query. The high level of agreement between the aboutness decisions based on functional relations and the subject specialists\u27 decisions demonstrates clearly the consistency of language behavior in relevance assessments where the definition on which the decisions are made is aboutness or match in topic. These conclusions have implications for indexing systems, query negotiation, search strategy formation, retrieval system research and the development of interface mechanisms for on-line retrieval systems

Theoretical evaluation of XML retrieval

This thesis develops a theoretical framework to evaluate XML retrieval. XML retrieval deals with retrieving those document parts that specifically answer a query. It is concerned with using the document structure to improve the retrieval of information from documents by only delivering those parts of a document an information need is about. We define a theoretical evaluation methodology based on the idea of `aboutness' and apply it to XML retrieval models. Situation Theory is used to express the aboutness proprieties of XML retrieval models. We develop a dedicated methodology for the evaluation of XML retrieval and apply this methodology to five XML retrieval models and other XML retrieval topics such as evaluation methodologies, filters and experimental results

Children’s information retrieval: beyond examining search strategies and interfaces

The study of children’s information retrieval is still for the greater part untouched territory. Meanwhile, children can become lost in the digital information world, because they are confronted with search interfaces, both designed by and for adults. Most current research on children’s information retrieval focuses on examining children’s search performance on existing search interfaces to determine what kind of interfaces are suitable for children’s search behaviour. However, to discover the true nature of children’s search behaviour, we state that research has to go beyond examining search strategies used with existing search interfaces by examining children’s cognitive processes during information-seeking. A paradigm of children’s information retrieval should provide an overview of all the components beyond search interfaces and search strategies that are part of children’s information retrieval process. Better understanding of the nature of children’s search behaviour can help adults design interfaces and information retrieval systems that both support children’s natural search strategies and help them find their way in the digital information world

TEMU KEMBALI INFORMASI DARI SUDUT PANDANG PENDEKATAN BERORIENTASI PEMAKAI

User oriented approach is a systematic study of users’ characteristics and behaviours to find information concerning its interaction with information systems (instutions). Basically there are three approaches to the study of information retrival processes, namely traditional approach, user oriented, and cognitif approach. The user-oriented approach to information retrieval research provides information retrieval theory with a substantial insight into users’ mental behaviour and information seeking characteristics. This approach focusses itself on the psychological and behavioral aspects of the communication between users and authors. This approach aims at the improvement of information retrieval effectiveness within the framework of the users, their information need, and the interactive processes of searching behaviour. But, this interaction process still could not solve the users’ problems. This is caused by the interation between information retrieval technique using matching system and clossed questions. In order to get more evidence about users problems or information need, further questions or feedback from the user in order to know whether intermediary interpretation match with the user’s or not are needed. The user oriented approach is still connected to information systems so that it is considered to have the same shortcoming as the traditional approach is. This reason caused the cognitive approach to appear

The Lifeworld in the Library\u27s Backroom: A Hermeneutic Phenomenological Study of the Cataloguer\u27s Lived Experience of Aboutness Determination

This research is interested in the cataloguer\u27s lived experience of aboutness determination. Aboutness determination, a part of subject cataloguing where the cataloguer attempts to identify the subject matter of a resource, is a process often taken for granted and largely neglected by the library community. Yet, aboutness determination is an essential stage in subject cataloguing worthy of greater attention. There is a need for a deeper understanding of the cataloguer\u27s relatedness to the resource in aboutness determination. This hermeneutic phenomenological study examines the lifeworld of three professional cataloguers. Through in-depth, semi-structured interviews and through talk-aloud analysis of resources, the interpreted findings provide access to the lived experience of cataloguers in aboutness determination, thus providing insight into this phenomenon. What is revealed is that aboutness determination involves a variable encounter, predisposed by systems and structures, in which the cataloguer acts as an intermediate agent in consideration of the resource and the user. The signification of this understanding is thoughtfulness. It is to give heed to the experience as it is, and to illuminate the essential qualities of that experience so that it may be understood more fully

Lexical measurements for information retrieval: a quantum approach

The problem of determining whether a document is about a loosely defined topic is at the core of text Information Retrieval (IR). An automatic IR system should be able to determine if a document is likely to convey information on a topic. In most cases, it has to do it solely based on measure- ments of the use of terms in the document (lexical measurements). In this work a novel scheme for measuring and representing lexical information from text documents is proposed. This scheme is inspired by the concept of ideal measurement as is described by Quantum Theory (QT). We apply it to Information Retrieval through formal analogies between text processing and physical measurements. The main contribution of this work is the development of a complete mathematical scheme to describe lexical measurements. These measurements encompass current ways of repre- senting text, but also completely new representation schemes for it. For example, this quantum-like representation includes logical features such as non-Boolean behaviour that has been suggested to be a fundamental issue when extracting information from natural language text. This scheme also provides a formal unification of logical, probabilistic and geometric approaches to the IR problem. From the concepts and structures in this scheme of lexical measurement, and using the principle of uncertain conditional, an “Aboutness Witness” is defined as a transformation that can detect docu- ments that are relevant to a query. Mathematical properties of the Aboutness Witness are described in detail and related to other concepts from Information Retrieval. A practical application of this concept is also developed for ad hoc retrieval tasks, and is evaluated with standard collections. Even though the introduction of the model instantiated here does not lead to substantial perfor- mance improvements, it is shown how it can be extended and improved, as well as how it can generate a whole range of radically new models and methodologies. This work opens a number of research possibilities both theoretical and experimental, like new representations for documents in Hilbert spaces or other forms, methodologies for term weighting to be used either within the proposed framework or independently, ways to extend existing methodologies, and a new range of operator-based methods for several tasks in IR