Information Discovery System Research Articles

"It's not your tumblr": Commentary-style tagging practices in fandom communities

Tagging practices on online platforms prioritize descriptive elements that contribute to information discovery. As a secondary tagging practice, commentary tags expand the functionality of online tagging to incorporate creative and expressive elements that initially seem to contribute little to information discovery systems. These tags have gained popularity, particularly within online fan communities and their preferred platforms, such as the social media blogging site Tumblr. Although popularized on Tumblr, commentary-style tags have become a recognizable fandom practice across platforms that host fan communities, including the fan work repository platform Archive of Our Own. Examining fan use of commentary tags provides insight into how such tagging practices could broaden information discovery to incorporate elements of creator expression and deepen user engagement with information resources.

View of the Interface between Ethics and Metadata

Despite its advantages in improving access to information, metadata has the potential to cause harm, if used inappropriately. For instance, mass surveillance of phone calls can be used by intelligence agencies to target individuals. Language use can reinforce prejudices; poor language control undermines the efficiency of subject searches; and the opacity of discovery systems reduces the effectiveness of retrieval systems. There are also concerns about who owns the intellectual property associated with metadata creation. The talk concluded with a description of two proposed initiatives: by ISKO to investigate ways of improving metadata use in information discovery systems; and the recruitment for a fully-funded PhD studentship at Edinburgh Napier University to investigate the ethics of metadata.

A Secure Information Discovery Using Mobile Agents in Wireless Industry 4.0 Networks

Industry 4.0 became the boon to secure information discovery. In most existing information discovery systems, mobile computing processes are complex due to their continuous query processing overhead to provide “right information at right time.” Even though many searching applications are there, they are unable to provide the accurate information when needed as the required objects are not being updated regularly. This paper intends to provide a process and Industry 4.0 architectures, which performs a secure information and discovery database through securing the users query. The paper also deals with the responses to the respective query made by monitor tracker agent. The research work secures the information discovery using mobile agents in wireless Industry 4.0 networks.

Analysis on an Auto Increment Detection System of Chinese Disaster Weibo Text

With the rapid development of Internet information technology, the advantages of social media in terms of speed, content, form, and effect of communication are becoming increasingly significant. In recent years, more and more researchers have paid attention to the special value and role of social media tools in disaster information emergency management. Weibo is the most widely used Chinese social media tool. To effectively mine and apply the emergency function of disaster situation microblogs, a disaster situation information discovery and collection system capable of online incremental identification and collection are constructed for massive and disordered disaster microblog text streams. First, based on the deep learning- trained word vector model and a large-scale corpus, an unsupervised short-text feature representation method of disaster situation Weibo information is developed. According to the experimental results of the feature combination test and the training set scale test, the SVM algorithm was selected for disaster microblog information classification, which realized effective identification of disaster situation micro-bloggings. Then, the temporal information similarity and geographic information similarity are used to improve the single text similarity algorithm, and a Chinese disaster event online real-time detection model is constructed. Furthermore, the disaster-affected areas can be achieved in real-time based on the detection results. By crawling and classifying the micro-bloggings from the disaster-affected areas, it is possible to realize the incremental identification and collection of online disaster situation Weibo information. Finally, the empirical analysis of disaster events such as the “Leshan Earthquake” shows that the real- time intelligent identification and collection system for disaster situation Weibo micro-bloggings developed in this paper can obtain large-scale and useful data for disaster emergency management, which proving that this system is effective and efficient.

Social information discovery enhanced by sentiment analysis techniques

In recent years, the massive diffusion of social networks has made available a large amount of user-generated content, for the most part in the form of textual data that contain people’s thoughts and emotions about a great variety of topics. In order to exploit these publicly available information, in this work we introduce a social information discovery system which elaborates simultaneously over more-than-one social network in an integrated scenario. The system is designed to ensure flexibility and scalability, thus enabling for (near-)real-time analysis even in case of high rates of content’s creation and large amounts of heterogeneous data. Furthermore, a noise detection technique ensures a high relevance of analyzed posts/tweets to the domain of interest. We also propose a lexicon-based sentiment analysis algorithm to extract and measure users’ opinion, in order to support collaboration and open innovation. Polysemous words and negations are typically challenging for lexicon-based approaches: for this reason, we introduce both a word sense disambiguation algorithm and a negation handling technique. Experiments on several datasets have proven that the combined use of both techniques improves the classification accuracy on 3-class sentiment analysis.

Toward the Resistant Reading of Information: Google, Resistant Spectatorship, and Critical Information Literacy

The theory of resistant spectatorship posits that individuals interacting with media and information may have the agency or power to oppose, reject, or reassemble the message they encounter instead of passively accepting it. This study puts resistant spectatorship in conversation with information literacy and critiques one example of a dominant information discovery system, Google Search, from a “resistant” position. Additionally, this study argues that, within academic libraries, the practice of critical information literacy, a pedagogical approach aligned with the concept of resistant spectatorship, is an ideal mode for encouraging students to become resistant readers of information in its increasingly corporate-mediated forms.

How Google Uses Metadata to Improve Search Results

This article critically examines four Google search products (Google Advanced Search, Google News Advanced Search, Google Books Advanced Search, and Google Advanced Scholar Search) and shows how each uses metadata to enhance or improve search results. In addition, the article shows how metadata can increase search precision and recall in information discovery systems. From a library perspective, this article analyzes some of the metadata-enabled features of Google's advanced search pages and compares these features to those found in a typical online library catalog. From a serials perspective, Google News Advanced Search demonstrates how Google indexes news websites, sites that are essentially continuing resources. As Google incorporates more and more metadata functionality into its advanced search pages, they increasingly begin to function more like online library catalogs and less like search pages found in a traditional Internet search engine. The simple search box has many limitations, and like libraries, Google is increasingly creating and offering metadata-enabled search features that improve search precision and recall in its products.

The Intersection of Virtual Organizations and the Library: A Case Study

The proliferation of virtual organizations is changing the nature and practice of research. These changes present a challenge to Libraries, as their traditional roles and services do not translate well to virtual organizations. However, virtual organizations also offer opportunities for librarians to participate in shaping the next generation of information discovery and management systems. This case study describes a project conducted by the Purdue University Libraries to assist CAT-hub, a developing virtual organization, in creating a set of tags for information discovery and site navigation. The methodology and processes used to develop and implement these tags are described in detail.

Squid: Enabling search in DHT-based systems

A fundamental problem in large scale, decentralized distributed systems is the efficient discovery of information. This paper presents Squid, a peer-to-peer information discovery system that supports flexible searches and provides search guarantees. The fundamental concept underlying the approach is the definition of multi-dimensional information spaces and the maintenance of locality in these spaces. The key innovation is a dimensionality reducing indexing scheme that effectively maps the multi-dimensional information space to physical peers while preserving lexical locality. Squid supports complex queries containing partial keywords, wildcards and ranges. Analytical and simulation results show that Squid is scalable and efficient.

Revisiting the foundations of information discovery and access systems

AbstractEach year, the pace of building digital resource and data repositories increases. Multiple challenges face each project, for which no adequate technological solution may exist. The focus of this panel moves beyond construction to address the question: What assumptions and principles lie beneath the technology scaffolding digital environments? The members of this panel are engaged in open exploration and reconsideration of the roles played by representational and organizational structures that seek to support, and which sometimes impair discovery, access and use. These structures take shape in metadata, vocabulary and classificatory frameworks. Specific topics covered will include heritage classificatory work well‐suited for application in digital environments, an inversion of the role of metadata as infrastructure for documents, application of bibliographic relationship taxonomies such as FRBR in tracking the life cycle of data objects, and potential definition and organizational roles to be played by collection level representations.

DIG--a system for gene annotation and functional discovery

We describe a database and information discovery system named DIG (Duke Integrated Genomics) designed to facilitate the process of gene annotation and the discovery of functional context. The DIG system collects and organizes gene annotation and functional information, and includes tools that support an understanding of genes in a functional context by providing a framework for integrating and visualizing gene expression, protein interaction and literature-based interaction networks.

Topic-specific crawling on the Web with the measurements of the relevancy context graph

One of the major problems for automatically constructed portals and information discovery systems is how to assign proper order to unvisited web pages. Topic-specific crawlers and information seeking agents should try not to traverse the off-topic areas and concentrate on links that lead to documents of interest. In this paper, we propose an effective approach based on the relevancy context graph to solve this problem. The graph can estimate the distance and the relevancy degree between the retrieved document and the given topic. By calculating the word distributions of the general and topic-specific feature words, our method will preserve the property of the relevancy context graph and reflect it on the word distributions. With the help of topic-specific and general word distribution, our crawler can measure a page's expected relevancy to a given topic and determine the order in which pages should be visited first. Simulations are also performed, and the results show that our method outperforms than the breath-first and the method using only the context graph.

Enabling flexible queries with guarantees in p2p systems

The Squid peer-to-peer information discovery system supports flexible queries using partial keywords, wildcards, and ranges. It is built on a structured overlay and uses data lookup protocols to guarantee that all existing data elements that match a query are found efficiently. Its main innovation is a dimension-reducing indexing scheme that effectively maps multidimensional information space to physical peers.

What is information discovery about?

The Internet has led to an increase in the quantity and diversity of information available for searching. Furthermore, users are bombarded by a constant barrage of electronic messages in the form of e-mail, faxes, etc. This has led to a plethora of search engines, “intelligent” agents, etc., that aim to help users in their quest for relevant information, or shield them against irrelevant information. All these systems aim to identify the potentially relevant information in among a large pool of available information. No unifying underlying theory for information discovery systems exists as yet. The aim of this article is to provide a logic-based framework for information discovery, and relate this to the traditional field of information retrieval. Furthermore, the often ignored user receives special emphasis. In information discovery, a good understanding of a user's (sometimes hidden) needs and beliefs is essential. We will develop a logic-based approach to express the mechanics of information discovery, while the pragmatics are based on an analysis of the underlying informational semantics of information carriers and information needs of users.

What is information discovery about?

The Internet has led to an increase in the quantity and diversity of information available for searching. Furthermore, users are bombarded by a constant barrage of electronic messages in the form of e-mail, faxes, etc. This has led to a plethora of search engines, “intelligent” agents, etc., that aim to help users in their quest for relevant information, or shield them against irrelevant information. All these systems aim to identify the potentially relevant information in among a large pool of available information. No unifying underlying theory for information discovery systems exists as yet. The aim of this article is to provide a logic-based framework for information discovery, and relate this to the traditional field of information retrieval. Furthermore, the often ignored user receives special emphasis. In information discovery, a good understanding of a user's (sometimes hidden) needs and beliefs is essential. We will develop a logic-based approach to express the mechanics of information discovery, while the pragmatics are based on an analysis of the underlying informational semantics of information carriers and information needs of users.

Efficient searching for specific resources on the World-Wide Web: creation of a search server for radiologists.

Our objective was to develop an efficient way to search for radiology information on the World-Wide Web (WWW). With the Harvest Information Discovery and Access System and a DECstation 3000 computer, each week we gather and update WWW documents that relate to radiology. To limit the size of the gathered documents, certain data (such as image files) are omitted. To date, we have gathered from 20 main radiology sites. By accessing our server, thousands of documents can be efficiently searched for specific radiology information. At no charge, individuals with access to the WWW can request a search of our server for specific radiology information. We return to the requester in HyperText Markup Language a document with results of the search included as embedded pointers. Our server address, or uniform resource locator, is http://glimpse.cs.arizona.edu/radiology.html. Use of a server dedicated to radiology is an efficient way to search the internet for radiology resources, such as teaching files. We provide access to many sites with one search, and we select those sites to ensure that only relevant and timely information is gathered. We also index that information.

The Harvest information discovery and access system

It is increasingly difficult to make effective use of Internet information, given the rapid growth in data volume, user base, and data diversity. In this paper we introduce Harvest, a system that provides a scalable, customizable architecture for gathering, indexing, caching, replicating, and accessing Internet information.