Real Searches Research Articles

Spatial Search and Bayes Theorem: A Commentary on Recent Examples from Aircraft Accidents

This paper presents a Bayesian search methodology in the context of missing aircraft, as well as a few other related search operations. The search seeks an item hidden in one of n cells. The parameters controlling the search are the prior probabilities (updated during each phase of the search) and the search quality. Assume the search begins in the area with the maximal prior. The expected length of the search depends on how far the item is from that locale (in essence a measure of the quality of the prior), and the search effectiveness parameter. A perfect (error free) search could find the item in a number of steps as a function of the distance of the object from the starting location. Lower quality search can take a lot longer, though it can ultimately be effective. The Bayesian process works by guiding us to the higher likelihood areas based on the results of failed search. It adds value by eliminating unlikely possibilities. The search can have an element of luck in starting its exploration close to the actual item. Real searches, where this was true, were in fact ultimately successful; real searches which were not so fortunate ended in failure.

Upgrade of a current research information system with ontologically supported semantic search engine

Harmonising the metadata format alone does not solve the issue of efficient access to relevant information in heterogeneous environments, when different systems use different content, contextual and semantic concepts for certain entities. One such type of heterogeneous systems are also Current Research Information Systems (CRIS), which store their data primarily in local relational databases, using different formats and various local concepts.In this article, we study the possibilities and propose a new ontologically supported semantic search engine (OSSSE) which, in addition to the harmonisation of the metadata format among local CRIS systems, also ensures that the meaning of data and/or concepts that belong to various metadata entities are also harmonised. A special model of ontological infrastructure was designed, and dedicated test ontology was created alongside with a new simplified algorithm for creating ontology, the basis of which is the distinction between new and already existing classes in terms of content. Finally, we evaluated the proposed OSSSE model using a simulation of the search process on the base of 41,113 real searches within SICRIS. The obtained results show that regardless of the search situation, the proposed OSSSE is always at least as efficient as a search without ontological support in terms of precision, while recall remains the same; the improvement has been shown to be statistically significant with a high confidence interval (p<0.005).The proposed OSSSE model is able to solve the issue of harmonizing the data where different heterogeneous systems use different content, contextual and semantic concepts, which is the case in many advanced expert systems. In this manner, the more the search is carried out based on the properties described by the supporting ontology, the more the infrastructure can help a searcher. The proposed concepts, ontological infrastructure and the designed semantic search engine may well help to improve search precision in several information retrieval systems.

ENHANCED INTERFEROMETRIC IDENTIFICATION OF SPECTRA IN HABITABLE EXTRASOLAR PLANETS

An Earth-like extrasolar planet emits light that is many orders of magnitude fainter than that of the parent star. We propose a method of identifying bio-signature spectral lines in light of known extrasolar planets based on Fourier spectroscopy in the infrared, using an off-center part of a Fourier interferogram only. This results in superior sensitivity to narrower molecular-type spectral bands, which are expected in the planet spectrum but are absent in the parent star. We support this idea by numerical simulations that include photon and thermal noise, and show it to be feasible at a luminosity ratio of 10?6 for a Sun-like parent star in the infrared. We also carried out a laboratory experiment to illustrate the method. The results suggest that this method should be applicable to real planet searches.

Ontology-guided knowledge retrieval in an automobile assembly environment

In the body shop of an automobile assembly plant, having access to correct and timely information is very important in solving problems encountered in the assembly process. The Variation Reduction Adviser (VRA) system used within General Motors (GM) is a database containing problems encountered in this process and their possible solutions. The VRA acts as an electronic logbook that shares information across shifts within a plant as well as across multiple plants. The VRA also serves as a problem-solving tool by which solutions to problems encountered may be retrieved and reused. To function effectively as a problem-solving tool, it is important that relevant information is quickly retrieved from the VRA database. Traditionally, keyword-based retrieval strategies have been used. In these approaches, the user types in a list of words or phrases and those records in the database that contain those words or phrases exactly as typed are retrieved. The problem with this approach is that records containing words or phrases that are semantically related to the ones typed in but not exactly the same are not retrieved. For instance, if the user types “left-hand side,” the traditional keyword search will not find records that contain the abbreviation “LHS.” This paper describes a search mechanism based on a thesaurus (a simple version of an ontology) that overcomes this problem. It describes the standard criteria to measure the effectiveness of a search, defines a new criterion, and shows that in terms of these criteria, the ontology-guided approach gives better search results than the exact match mechanism. The results are shown in the context of real searches during the use of the VRA in a GM assembly plant.

Efficient Approximate Wordlength Optimization

In this paper, the problem of finding good wordlength combinations for fixed-point digital signal processing flowgraphs is addressed. By formulating and solving an approximate optimization problem, an estimated Pareto-optimal curve for attainable cost/quality combinations is rapidly calculated. This curve and the associated wordlength combinations are useful in several situations and can serve as starting points for real design searches. Examples that illustrate these concepts are given.

Relevance ranking is not relevance ranking or, when the user is not the user, the search results are not search results

PurposeThe purpose of this paper is to examine the significance of the differences between the actual technical principles determining relevance ranking, and how relevance ranking is understood, described and evaluated by the developers of relevance ranking algorithms and librarians.Design/methodology/approachThe discussion uses descriptions by PLWeb Turbo and C2 of their relevance ranking products and a librarian's description on her blog with the responses which it drew, contrasting these with relevancy as it is indicated in studies of the ISI citation record reported by White.FindingsThe study finds that product descriptions and librarians consistently use the term “relevance ranking” to mean both the artificial relevance ranking by statistical methods using various surrogates assumed to reliably indicate relevance and the real relevance as determined by the searcher. The paper indicates the misunderstandings arising from this terminological confusion and its consequences in the context of the invalid user models and artificial searches which accompany discussions of “relevance ranking”.Research limitations/implicationsEvaluations of relevance ranking must be based on real users and real searches. Theorising relevance as a judgement about information rather than a property of information clarifies many issues.Practical implicationsThe design of search engines and OPACs will benefit from incorporating metadata that contain indications of user‐determined relevance.Originality/valueThe activity of subject analysis and indexing by human beings is presented as an activity identical in kind to the real searcher's determination of relevance, a definite statement of relevancy arising from a real communication situation rather than a statistically indicated probability.

Term and citation retrieval: A field study

The relative efficacy of searching by terms and by citations is investigated with real searches collected in health sciences libraries. The objective is to seek evidence to confirm or refute findings from a controlled pilot study, and to understand the factors at work in operational search environments. Overall confirmation was found. In both the pilot and field studies, the improvement of the odds that overlap items retrieved would be relevant or partially relevant was truly astounding. If an item was retrieved from both MEDLINE ® and SCISEARCH ®, it was six times more likely that it would be relevant or partially relevant as opposed to being not relevant, and 8.4 times more likely for definitely relevant retrievals. In the field setting, citation searching was able to add an average of 24% recall to traditional subject retrieval. Term or citation searching from the open literature produced lower precision results. Attempts to identify distinguishing characteristics in queries which might benefit most from additional citation searches proved to be inconclusive. In spite of the obvious gain shown by citation searching, online access of citation databases has been hampered by their relative high cost.

Scatter of library and information science topics among bibliographic databases

Researchers and educators in library and information science borrow heavily from other disciplines and other disciplines make use of LIS concepts in organizing their own literatures. Materials relevant to LIS are scattered in the journals of many fields, and a search of one or two databases may miss relevant items. The purpose of this research was to begin to gather data to construct a mapping of LIS topics in non-LIS databases. Subject terms were taken at random from LISA, categorized, and put into BRS's CROSS database. A cluster analysis was conducted on the resulting 10.8 million postings to discover possible subject relationships among the databases. A search strategy was then developed using words which describe libraries, librarianship, and information science, and real searches conducted. A total of 168,673 hits were obtained and 2655 abstracts analyzed as to relevance. Precision estimates for each database tended to verify the clustering and gave further clues as to possibly fruitful search paths. The results showed that the clustering process is a useful starting point to characterize databases, and that there are many documents relevant to LIS in non-LIS databases. © 1990 John Wiley & Sons, Inc.