Java archives search engine using byte code as information source

This paper analyses user's behaviour for information retrieval using existing Web search engines and a search engine focusing on trend-related queries. We are developing a search engine focusing on trend-related queries, called context search engine which we expect available in various types of domains. We guessed that users represent their information needs as series of queries based on their search intentions when they use existing search engines. This paper explains that people use the context search engine in the same way as existing search engine and says the context search engine has same elements as existing search engines.

Discriminating meta-search: a framework for evaluation

Variation in Results of Three Biology‐Focused Search Engines: A Case Study Using North American Tree Species

With the exponential growth of the World Wide Web (WWW), it has become the most popular place to gather information. However the size of the WWW makes it difficult for people to locate relevant information. About 85% of all Web users use search engines of some kind for this purpose. However, existing search engines often do not return relevant information. The main focus of this paper is to improve search performance by using keywords and web pages which have been previously used or visited by other users. The Formal Concept Analysis (FCA) method has been adapted to maintain a concept map of keywords. This paper shows how both precision and recall has improved the specific-domain area, in which users can share the same knowledge.

Generally, search engines perform the ranking of web pages in an offline mode, which is after the web pages have been retrieved and stored in the database. The existing HITS algorithm (Kleinberg, 1996) operates in an offline mode to perform page rank calculation. In this project, we have implemented an online mode of page ranking for this algorithm. This will improve the overall performance of the Search Engine. This report describes the approach used to implement and test this algorithm. Comparison results performed against other existing search engines are also presented in this report. This is helpful in describing the efficiency of implemented algorithm.

Online forums provide peer-to-peer technical support for many user populations, including programmers struggling to master a new language. Programmers can help one another by uploading code samples to such a forum. Unfortunately, finding relevant code samples can prove difficult using existing search engines for large, diverse forums. Therefore, we have prototyped a new kind of code search engine for online forums that draws upon unsupervised machine learning in two ways. First, it displays code samples in visual groupings based on the mutual similarity of code samples. Second, it uses the assignment of code samples to clusters to achieve a form of query expansion, thereby identifying additional search results as potentially useful. We evaluated the system by running it on the forum for the LabVIEW programming language. A textual analysis of posts showed that the unsupervised machine learning algorithm successfully tended to assign code samples to clusters based on topical similarity. An empirical user evaluation confirmed that the new search engine improved on the forum's existing search engine by providing results for more queries, by generating more results per query, and by providing more relevant search results.

Crawling and indexing have been considered regarding existing search engines, but whereas high speed crawling has been studied widely, improvements in the speed of indexing have seldom been discussed. Building a fresh information search engine should, however, unify these arguments concerning crawling and indexing. In this report, an index updating process based on a pipeline that unifies crawling and indexing was proposed. The techniques of a distributed index updating process are discussed with regards to a distributed cooperative search engine.

The context search engine has been studied for answering trend-related queries. As trend information is obtained from temporal data, which is common in many applications, the context engine is expected to be available regardless of domains. When using existing search engines, it is supposed that users submit a series of queries based on search intention. Therefore, search functions of the context search engine should be designed based on the user’s potential search intention. To analyze user’s behavior in information retrieval, this paper conducted experiments using existing Web search engines. The experimental result is analyzed, based on which the design of a context search engine is described. As another contribution of this paper, new types of temporal variations which can be used to specify queries of the context search engine are also proposed. The results of user experiments confirmed the usability of the proposed temporal variations.

In companies a large amount of information is maintained that is accessible via network communication tools. This makes searching for a particular piece of information a difficult task. We identified two major difficulties that are experienced using existing search engines. These difficulties are that many of the existing search engines only take syntactic information into account and therefore do not find all relevant documents, and that many of the retrieved documents do not contain relevant information. We present a search engine that tackles both of these problems. The system, Dwebic, is based on a description logic knowledge base that deals with strict taxonomic information as well as with default information. We define this description logic and introduce a new kind of inference. Dwebic has a World Wide Web interface, but our approach does not depend on the World Wide Web.

An investigation of multiple devices and information sources used in the hotel booking process

Internet has become an instant source of informatio n for almost anyone. By viewing the results of sear ch terms displayed by an Internet Search Engine (ISE), a person may decide his next course of action whether to continue using the Internet, abort or to combine it with other sources of information. The results produced by an ISE can be regarded as an in dex of relative availability of references. Given a list of suitable search terms, a user will firstly have to decide on the ISE to be used. Due to huge potent ial references available for given search terms the use r has to create heuristics to choose the entries sh own on the computer screen. As there are varying breadths and depths of information revealed by various Inter net Search Engines (ISE’s), this paper will not attempt to make a comparison among ISE’s, rather will focu s only on a particular search engine and ascertain th e results it produces given a list of search terms. Google is chosen as a proxy, being one of the most popular ISE’s. By confining to only a search engine, the s tudy affords to control variability among ISE’s should m ultiple ISE’s be used. With the search engine place d under control, it is easy to achieve the primary ob jective of the study, i.e., to ascertain availabili ty of relative breadth of sub-themes of Analytic Hierarch y Process (AHP) in Google. It is natural for user, especially researcher to be concerned with number, quantity. If there is seemingly abundant literature , one would be motivated to pursue research along the the me or sub-theme. In this study, the strength of presence of a sub-theme is measured by using two measures: (i) result of a sub-theme of AHP over the sub-theme itself, and (ii) result of the sub-theme over the total results generated for all of the thi rty six sub-themes used in the search. This study controlle d biasness in specifying the sub-themes of AHP by adopting the sub-themes or search terms specified b y the 2013 AHP conference organizers. This decision helps make the study efficient without with it has to distill the sub-themes by surveying the AHP literature. The data for analysis was gathered by s urfing Google on 26 Feb 2013 8.55 p.m. - 9.26 p.m. Peninsular Malaysian time. The search results were computed to generate two types of ratios specified earlier. A composite index was created using the re sulting two types of ratios which are used to class ify the efficiency, hence dominance of the original res ults (hits). Kendall’s correlation produced statist ically significant correlations between the composite inde x and Rank of AHP specific and area results. Using indices greater than 1.000 as the base, 6 AHP specific areas occupy the top positions with ratios ranging from 19.341 to 61.574; 15 AHP specific areas occupy the second top positions with ratios ranging from 1.119 to 9.602, and 14 AHP specific areas occupy the third and last position with indi ces below 1.000 ranging from 0.050 to 0.894. The paper includes dis cussion, implications, limitations, conclusions and suggestions for further research.

Background:Occupational Safety and Health (OSH) professionals must base their advice and interventions on evidence from science, in balance with their expertise, and with workers’ and other stakeholders’ values and preferences. Evidence-based professional practice is one of the remedies against misinformation creating confusion and distrust in the society.Objectives:To present, for OSH professionals, an overview and critical considerations about concepts, strategies, and tools needed for an accurate search for evidence-based information.Methods:Information sources have been collected and discussed as a base for a documented vision on knowledge questions, online information sources, search engines, databases, and tools.Results:Every search should start with a carefully phrased question. To help finding a reliable answer, potential evidence-based online sources are presented. Systematic reviews and original scientific articles are regarded as primary sources. Secondary and tertiary sources are discussed, such as practice guidelines, point-of-care summaries, advisory reports, quality websites or apps, Wikipedia, quality videos, and e-lessons. To find sources, adequate use of search engines and databases is required. Examples are discussed briefly, such as PubMed/MEDLINE, Virtual Health Library, NICE, Cochrane Library, Cochrane Work, Google (Scholar), and YouTube.Conclusions:Evidence-based practice in OSH must be stimulated, relying mainly on trusted online sources. The breadth of appropriate information sources is wider than described in most publications. Search engines facilitate the finding of quality reports, videos, e-courses, and websites. Such sources can be explored by well-trained professionals to complement the use of scientific articles, reviews, point-of-care summaries, and guidelines. Adequate use of online information sources requires awareness, motivation, and skills in professionals and educators. To date, the quality of skills in searching is low, thus a more adequate education is crucial. The quality of sources, search engines, and databases will be considered more thoroughly in another study. International collaboration is profitable and needs new drivers.

Variability of patient spine education by Internet search engine

An important software engineering artefact used by developers and maintainers to assist in software comprehension and maintenance is source code documentation. It provides insights that help software engineers to effectively perform their tasks, and therefore ensuring the quality of the documentation is extremely important. Inline documentation is at the forefront of explaining a programmer’s original intentions for a given implementation. Since this documentation is written in natural language, ensuring its quality needs to be performed manually. In this paper, we present an effective and automated approach for assessing the quality of inline documentation using a set of heuristics, targeting both quality of language and consistency between source code and its comments. We apply our tool to the different modules of two open source applications (ArgoUML and Eclipse), and correlate the results returned by the analysis with bug defects reported for the individual modules in order to determine connections between documentation and code quality.

Modern society receives a relatively big part of information using information communication devices. Information search possibilities are rapidly growing. On the other hand, the amount of information itself is expanding. One of the quickest ways of finding information is using internet search engines, e.g., “Google”, “Yahoo”, “AltaVista” and others. Their usage undoubtedly makes big influence on education. Pupils’ ability to find the necessary information is highly relevant. Thus, information search literacy is an inseparable component of general education. It is not enough only to find information, it is necessary to use it in the most effective way. Seeking to improve pupils’ information skills, it is necessary to know current position of an analysed question. The object of this research is information search using ICT. The aim of the research is to analyse how comprehensive school upper class students use ICT for information search. It has been ascertained by a research what additional information sources pupils use, where and how they get necessary literature, what information search engines and what electronic information sources they use most frequently. At least a few times per week apart from textbooks respondents use other literature as well (books, dictionaries, handbooks) for learning purposes. They use encyclopaedias very seldom or don’t use them at all. Pupils usually read books and newspapers which they have at home. They also use internet and library service; however, it is not popular to borrow books from friends or buy them. Pupils use internet daily both for leisure and learning. Girls more often than boys use internet for learning and for leisure – they use it equally. Respondents usually search information through Google search engine, less frequently – through Delfi. The other search engines and catalogues mentioned in the questionnaire are used very seldom, especially HotBot, Penki, On.lt and others. Both girls and boys, town and region pupils equally use search engines and catalogues. From electronic information sources respondents most frequently use internet encyclopaedia Wikipedia. Internet books and e magazines are read once a month on average, virtual library is scarcely used. It is absolutely not popular to use such sources as Nerandu.lt, tingiu.lt, Speros.lt. Key words: comprehensive school, electronic information sources, ICT, information search.