Search results

Dirk Ahlers studied computer science at the Carl-von-Ossietzky-University Oldenburg, Germany. In 2005, he started working as a research assistant at the OFFIS Institute for Information Technology, Oldenburg where he conducted projects in mobility and geospatial retrieval. While working at OFFIS, he also pursued his PhD with a topic in geographic information retrieval. He is currently working at UNITEC, a private university in Tegucigalpa, Honduras where he researches potential for local search for the case of a country with little Web coverage, challenging informal address schemes, and uncertain location data. His research interests are geospatial Web information retrieval, search engines, location-based services, Web technology, mobility, and everything geo. E-mail: dirk@dhere.de

Purpose — The purpose of this chapter is to give an overview of the context of Web search and search engine related research, as well as to introduce the reader to the sections and chapters of the book.

Methodology/approach — We review literature dealing with various aspects of search engines, with special emphasis on emerging areas of Web searching, search engine evaluation going beyond traditional methods and new perspectives on Web searching.

Findings — The approaches to studying Web search engines are manifold. Given the importance of Web search engines for knowledge acquisition, research from different perspectives needs to be integrated into a more cohesive perspective.

Research limitations/implications — The chapter suggests a basis for research in the field and also introduces further research directions.

Originality/value of paper — The chapter gives a concise overview of the topics dealt within the book and also shows directions for researchers interested in Web search engines.

This chapter outlines how search engine technology can be used in online public access catalogs (OPACs) to help improve users’ experiences, to identify users’ intentions, and to indicate how it can be applied in the library context, along with how sophisticated ranking criteria can be applied to the online library catalog. A review of the literature and the current OPAC developments forms the basis of recommendations on how to improve OPACs. Findings were that the major shortcomings of current OPACs are that they are not sufficiently user-centered and that their results presentations lack sophistication. Furthermore, these shortcomings are not addressed in current 2.0 developments. It is argued that OPAC development should be made search-centered before additional features are applied. Although the recommendations on ranking functionality and the use of user intentions are only conceptual and not yet applied to a library catalogue, practitioners will find recommendations for developing better OPACs in this chapter. In short, readers will find a systematic view on how the search engines’ strengths can be applied to improving libraries’ online catalogs.

Purpose — To provide a theoretical background to understand current local search engines as an aspect of specialized search, and understand the data sources and used technologies.

Design/methodology/approach — Selected local search engines are examined and compared toward their use of geographic information retrieval (GIR) technologies, data sources, available entity information, processing, and interfaces. An introduction to the field of GIR is given and its use in the selected systems is discussed.

Findings — All selected commercial local search engines utilize GIR technology in varying degrees for information preparation and presentation. It is also starting to be used in regular Web search. However, major differences can be found between the different search engines.

Research limitations/implications — This study is not exhaustive and only uses informal comparisons without definitive ranking. Due to the unavailability of hard data, informed guesses were made based on available public interfaces and literature.

Practical implications — A source of background information for understanding the results of local search engines, their provenance, and their potential.

Originality/value — An overview of GIR technology in the context of commercial search engines integrates research efforts and commercial systems and helps to understand both sides better.

Purpose — To develop methodologies to evaluate search engines according to an individual's preference in an easy and reliable manner, and to formulate user-oriented metrics to compare freshness and duplication in search results.

Design/methodology/approach — A personalised evaluation model for comparing search engines is designed as a hierarchy of weighted parameters. These commonly found search engine features and performance measures are given quantitative and qualitative ratings by an individual user. Furthermore, three performance measurement metrics are formulated and presented as histograms for visual inspection. A methodology is introduced to quantitatively compare and recognise the different histogram patterns within the context of search engine performance.

Findings — Precision and recall are the fundamental measures used in many search engine evaluations due to their simplicity, fairness and reliability. Most recent evaluation models are user oriented and focus on relevance issues. Identifiable statistical patterns are found in performance measures of search engines.

Research limitations/implications — The specific parameters used in the evaluation model could be further refined. A larger scale user study would confirm the validity and usefulness of the model. The three performance measures presented give a reasonably informative overview of the characteristics of a search engine. However, additional performance parameters and their resulting statistical patterns would make the methodology more valuable to the users.

Practical implications — The easy-to-use personalised search engine evaluation model can be tailored to an individual's preference and needs simply by changing the weights and modifying the features considered. A user is able to get an idea of the characteristics of a search engine quickly using the quantitative measure of histogram patterns that represent the search performance metrics introduced.

Originality/value — The presented work is considered original as one of the first search engine evaluation models that can be personalised. This enables a Web searcher to choose an appropriate search engine for his/her needs and hence finding the right information in the shortest time with the least effort.