Towards automated information retrieval of process data and knowledge from academic databases

Process modeling requires both data (chemical reaction yields, kinetic constants, cost estimates, environmental indicators, etc.) and knowledge (operation models and formulations, alternative processes and technologies, etc.). Searching in databases and published research may provide such information, but there is a lack of systematic methods and tools guiding this procedure. The present work describes and assesses an information retrieval methodology that is part of a proposed retrieval and extraction cycle addressing this problem. Two query construction methods for sampling academic databases are proposed, assessed and compared. Departing from a seed corpus of a limited number of papers, Scopus® is used as an academic database to retrieve literature containing information associated with pyrolysis processes of waste plastic. It is found that, with minimal human intervention, the methodology is able to return a ranked list of candidate documents that have a considerable (linguistic) relevance.Postprint (published version

Searching for information on the web: A guideline for effective searching

To date, the World Wide Web (WWW) is the most popular environment for information searching and retrieval. One of the steps in searching for information on the web is by entering a query to the search system and reformulating the queries. There are many challenges and issues in formulating effective queries. Effective queries will produce relevant document that matches the user information need. The discussion of this chapter will be focusing on how to apply both breadth and depth search query formulation strategies for effective searching on the web. The discussion will be based on a selected search task. At the end of the chapter, a recommendation for a step-by-step searching procedure will be presented as a guideline for effective searching

Personalized online information search and visualization

BACKGROUND: The rapid growth of online publications such as the Medline and other sources raises the questions how to get the relevant information efficiently. It is important, for a bench scientist, e.g., to monitor related publications constantly. It is also important, for a clinician, e.g., to access the patient records anywhere and anytime. Although time-consuming, this kind of searching procedure is usually similar and simple. Likely, it involves a search engine and a visualization interface. Different words or combination reflects different research topics. The objective of this study is to automate this tedious procedure by recording those words/terms in a database and online sources, and use the information for an automated search and retrieval. The retrieved information will be available anytime and anywhere through a secure web server. RESULTS: We developed such a database that stored searching terms, journals and et al., and implement a piece of software for searching the medical subject heading-indexed sources such as the Medline and other online sources automatically. The returned information were stored locally, as is, on a server and visible through a Web-based interface. The search was performed daily or otherwise scheduled and the users logon to the website anytime without typing any words. The system has potentials to retrieve similarly from non-medical subject heading-indexed literature or a privileged information source such as a clinical information system. The issues such as security, presentation and visualization of the retrieved information were thus addressed. One of the presentation issues such as wireless access was also experimented. A user survey showed that the personalized online searches saved time and increased and relevancy. Handheld devices could also be used to access the stored information but less satisfactory. CONCLUSION: The Web-searching software or similar system has potential to be an efficient tool for both bench scientists and clinicians for their daily information needs

Dublin City University video track experiments for TREC 2002

Dublin City University participated in the Feature Extraction task and the Search task of the TREC-2002 Video Track. In the Feature Extraction task, we submitted 3 features: Face, Speech, and Music. In the Search task, we developed an interactive video retrieval system, which incorporated the 40 hours of the video search test collection and supported user searching using our own feature extraction data along with the donated feature data and ASR transcript from other Video Track groups. This video retrieval system allows a user to specify a query based on the 10 features and ASR transcript, and the query result is a ranked list of videos that can be further browsed at the shot level. To evaluate the usefulness of the feature-based query, we have developed a second system interface that provides only ASR transcript-based querying, and we conducted an experiment with 12 test users to compare these 2 systems. Results were submitted to NIST and we are currently conducting further analysis of user performance with these 2 systems

Chemoinformatics Research at the University of Sheffield: A History and Citation Analysis

This paper reviews the work of the Chemoinformatics Research Group in the Department of Information Studies at the University of Sheffield, focusing particularly on the work carried out in the period 1985-2002. Four major research areas are discussed, these involving the development of methods for: substructure searching in databases of three-dimensional structures, including both rigid and flexible molecules; the representation and searching of the Markush structures that occur in chemical patents; similarity searching in databases of both two-dimensional and three-dimensional structures; and compound selection and the design of combinatorial libraries. An analysis of citations to 321 publications from the Group shows that it attracted a total of 3725 residual citations during the period 1980-2002. These citations appeared in 411 different journals, and involved 910 different citing organizations from 54 different countries, thus demonstrating the widespread impact of the Group's work

Which one is better: presentation-based or content-based math search?

Mathematical content is a valuable information source and retrieving this content has become an important issue. This paper compares two searching strategies for math expressions: presentation-based and content-based approaches. Presentation-based search uses state-of-the-art math search system while content-based search uses semantic enrichment of math expressions to convert math expressions into their content forms and searching is done using these content-based expressions. By considering the meaning of math expressions, the quality of search system is improved over presentation-based systems

The effect of dyslexia on information retrieval: A pilot study

Purpose – The purpose of the paper is to resolve a gap in our knowledge of how people with dyslexia interact with Information Retrieval (IR) systems, specifically an understanding of their information searching behaviour. Very little research has been undertaken with this particular user group, and given the size of the group (an estimated 10% of the population) this lack of knowledge needs to be addressed. Design/Methodology/Approach - We use elements of the dyslexia cognitive profile to design a logging system recording the difference between two sets of participants: dyslexic and control users. We use a standard Okapi interface together with two standard TREC topics in order to record the information searching behaviour of these users. We gather evidence from various sources, including quantitative information on search logs, together with qualitative information from interviews and questionnaires. We record variables on queries, documents, relevance assessments and sessions in the search logs. We use this evidence to examine the difference in searching between the two sets of users, in order to understand the effect of dyslexia on the information searching behaviour. A topic analysis is also conducted on the quantitative data to show any effect on the results from the information need. Research limitations/implications – As this is a pilot study, only 10 participants were recruited for the study, 5 for each user group. Due to ethical issues, the number of topics per search was restricted to one topic only. The study shows that the methodology applied is useful for distinguishing between the two user groups, taking into account differences between topic. We outline further research on the back of this pilot study in four main areas. A different approach from the proposed methodology is needed to measure the effect on query variables, which takes account of topic variation. More details on users are needed such as reading abilities, speed of language processing and working memory to distinguish the user groups. Effect of topic on search interaction must be measured in order to record the potential impact on the dyslexic user group. Work is needed on relevance assessment and effect on precision and recall for users who may not read many documents. Findings – Using the log data, we establish the differences in information searching behaviour of control and dyslexic users i.e. in the way the two groups interact with Okapi, and that qualitative information collected (such as experience etc) may not be able to account for these differences. Evidence from query variables was unable to distinguish between groups, but differences on topic for the same variables were recorded. Users who view more documents tended to judge more documents as being relevant, either in terms of the user group or topic. Session data indicated that there may be an important difference between the number of iterations used in a search between the user groups, as there may be little effect from the topic on this variable. Originality/Value – This is the first study of the effect of dyslexia on information search behaviour, and provides some evidence to take the field forward

The study of probability model for compound similarity searching

Information Retrieval or IR system main task is to retrieve relevant documents according to the users query. One of IR most popular retrieval model is the Vector Space Model. This model assumes relevance based on similarity, which is defined as the distance between query and document in the concept space. All currently existing chemical compound database systems have adapt the vector space model to calculate the similarity of a database entry to a query compound. However, it assumes that fragments represented by the bits are independent of one another, which is not necessarily true. Hence, the possibility of applying another IR model is explored, which is the Probabilistic Model, for chemical compound searching. This model estimates the probabilities of a chemical structure to have the same bioactivity as a target compound. It is envisioned that by ranking chemical structures in decreasing order of their probability of relevance to the query structure, the effectiveness of a molecular similarity searching system can be increased. Both fragment dependencies and independencies assumption are taken into consideration in achieving improvement towards compound similarity searching system. After conducting a series of simulated similarity searching, it is concluded that PM approaches really did perform better than the existing similarity searching. It gave better result in all evaluation criteria to confirm this statement. In terms of which probability model performs better, the BD model shown improvement over the BIR model

Relaxed lightweight assembly retrieval using vector space model

International audienceAssembly searching technologies are important for the improvement of design reusability. However, existing methods require that assemblies possess high-level information, and thus cannot be applied in lightweight assemblies. In this paper, we propose a novel relaxed lightweight assembly retrieval approach based on a vector space model (VSM). By decomposing the assemblies represented in a watertight polygon mesh into bags of parts, and considering the queries as a vague specification of a set of parts, the resilient ranking strategy in VSM is successfully applied in the assembly retrieval. Furthermore, we take the scale-sensitive similarities between parts into the evaluation of matching values, and extend the original VSM to a relaxed matching framework. This framework allows users to input any fuzzy queries, is capable of measuring the results quantitatively, and performs well in retrieving assemblies with specified characteristics. To accelerate the online matching procedure, a typical parts based matching process, as well as a greedy strategy based matching algorithm is presented and integrated in the framework, which makes our system achieve interactive performance. We demonstrate the efficiency and effectiveness of our approach through various experiments on the prototype system

Disambiguation strategies for cross-language information retrieval

This paper gives an overview of tools and methods for Cross-Language Information Retrieval (CLIR) that are developed within the Twenty-One project. The tools and methods are evaluated with the TREC CLIR task document collection using Dutch queries on the English document base. The main issue addressed here is an evaluation of two approaches to disambiguation. The underlying question is whether a lot of effort should be put in finding the correct translation for each query term before searching, or whether searching with more than one possible translation leads to better results? The experimental study suggests that the quality of search methods is more important than the quality of disambiguation methods. Good retrieval methods are able to disambiguate translated queries implicitly during searching