Evaluating Information Retrieval and Access Tasks

This open access book summarizes the first two decades of the NII Testbeds and Community for Information access Research (NTCIR). NTCIR is a series of evaluation forums run by a global team of researchers and hosted by the National Institute of Informatics (NII), Japan. The book is unique in that it discusses not just what was done at NTCIR, but also how it was done and the impact it has achieved. For example, in some chapters the reader sees the early seeds of what eventually grew to be the search engines that provide access to content on the World Wide Web, today’s smartphones that can tailor what they show to the needs of their owners, and the smart speakers that enrich our lives at home and on the move. We also get glimpses into how new search engines can be built for mathematical formulae, or for the digital record of a lived human life. Key to the success of the NTCIR endeavor was early recognition that information access research is an empirical discipline and that evaluation therefore lay at the core of the enterprise. Evaluation is thus at the heart of each chapter in this book. They show, for example, how the recognition that some documents are more important than others has shaped thinking about evaluation design. The thirty-three contributors to this volume speak for the many hundreds of researchers from dozens of countries around the world who together shaped NTCIR as organizers and participants. This book is suitable for researchers, practitioners, and students—anyone who wants to learn about past and present evaluation efforts in information retrieval, information access, and natural language processing, as well as those who want to participate in an evaluation task or even to design and organize one

ir_metadata: An Extensible Metadata Schema for IR Experiments

The information retrieval (IR) community has a strong tradition of making the computational artifacts and resources available for future reuse, allowing the validation of experimental results. Besides the actual test collections, the underlying run files are often hosted in data archives as part of conferences like TREC, CLEF, or NTCIR. Unfortunately, the run data itself does not provide much information about the underlying experiment. For instance, the single run file is not of much use without the context of the shared task's website or the run data archive. In other domains, like the social sciences, it is good practice to annotate research data with metadata. In this work, we introduce ir_metadata - an extensible metadata schema for TREC run files based on the PRIMAD model. We propose to align the metadata annotations to PRIMAD, which considers components of computational experiments that can affect reproducibility. Furthermore, we outline important components and information that should be reported in the metadata and give evidence from the literature. To demonstrate the usefulness of these metadata annotations, we implement new features in repro_eval that support the outlined metadata schema for the use case of reproducibility studies. Additionally, we curate a dataset with run files derived from experiments with different instantiations of PRIMAD components and annotate these with the corresponding metadata. In the experiments, we cover reproducibility experiments that are identified by the metadata and classified by PRIMAD. With this work, we enable IR researchers to annotate TREC run files and improve the reuse value of experimental artifacts even further.Comment: Resource pape

Joint Upper & Lower Bound Normalization for IR Evaluation

In this paper, we present a novel perspective towards IR evaluation by proposing a new family of evaluation metrics where the existing popular metrics (e.g., nDCG, MAP) are customized by introducing a query-specific lower-bound (LB) normalization term. While original nDCG, MAP etc. metrics are normalized in terms of their upper bounds based on an ideal ranked list, a corresponding LB normalization for them has not yet been studied. Specifically, we introduce two different variants of the proposed LB normalization, where the lower bound is estimated from a randomized ranking of the corresponding documents present in the evaluation set. We next conducted two case-studies by instantiating the new framework for two popular IR evaluation metric (with two variants, e.g., DCG_UL_V1,2 and MSP_UL_V1,2 ) and then comparing against the traditional metric without the proposed LB normalization. Experiments on two different data-sets with eight Learning-to-Rank (LETOR) methods demonstrate the following properties of the new LB normalized metric: 1) Statistically significant differences (between two methods) in terms of original metric no longer remain statistically significant in terms of Upper Lower (UL) Bound normalized version and vice-versa, especially for uninformative query-sets. 2) When compared against the original metric, our proposed UL normalized metrics demonstrate higher Discriminatory Power and better Consistency across different data-sets. These findings suggest that the IR community should consider UL normalization seriously when computing nDCG and MAP and more in-depth study of UL normalization for general IR evaluation is warranted.Comment: 26 pages, 3 figure

On Term Selection Techniques for Patent Prior Art Search

A patent is a set of exclusive rights granted to an inventor to protect his invention for a limited period of time. Patent prior art search involves finding previously granted patents, scientific articles, product descriptions, or any other published work that may be relevant to a new patent application. Many well-known information retrieval (IR) techniques (e.g., typical query expansion methods), which are proven effective for ad hoc search, are unsuccessful for patent prior art search. In this thesis, we mainly investigate the reasons that generic IR techniques are not effective for prior art search on the CLEF-IP test collection. First, we analyse the errors caused due to data curation and experimental settings like applying International Patent Classification codes assigned to the patent topics to filter the search results. Then, we investigate the influence of term selection on retrieval performance on the CLEF-IP prior art test collection, starting with the description section of the reference patent and using language models (LM) and BM25 scoring functions. We find that an oracular relevance feedback system, which extracts terms from the judged relevant documents far outperforms the baseline (i.e., 0.11 vs. 0.48) and performs twice as well on mean average precision (MAP) as the best participant in CLEF-IP 2010 (i.e., 0.22 vs. 0.48). We find a very clear term selection value threshold for use when choosing terms. We also notice that most of the useful feedback terms are actually present in the original query and hypothesise that the baseline system can be substantially improved by removing negative query terms. We try four simple automated approaches to identify negative terms for query reduction but we are unable to improve on the baseline performance with any of them. However, we show that a simple, minimal feedback interactive approach, where terms are selected from only the first retrieved relevant document outperforms the best result from CLEF-IP 2010, suggesting the promise of interactive methods for term selection in patent prior art search

Sounding Together

Sounding Together: Collaborative Perspectives on U.S. Music in the Twenty-21st Century is a multi-authored, collaboratively conceived book of essays that tackles key challenges facing scholars studying music of the United States in the early twenty-first century. This book encourages scholars in music circles and beyond to explore the intersections between social responsibility, community engagement, and academic practices through the simple act of working together. The book’s essays—written by a diverse and cross-generational group of scholars, performers, and practitioners—demonstrate how collaboration can harness complementary skills and nourish comparative boundary-crossing through interdisciplinary research. The chapters of the volume address issues of race, nationalism, mobility, cultural domination, and identity; as well as the crisis of the Trump era and the political power of music. Each contribution to the volume is written collaboratively by two scholars, bringing together contributors who represent a mix of career stages and positions. Through the practice of and reflection on collaboration, Sounding Together breaks out of long-established paradigms of solitude in humanities scholarship and works toward social justice in the study of music

Risk Mitigation, Vulnerability Management and Resilience under Disasters

The Special Issue (SI) discusses the topic of Disaster Risk Management and its cornerstones: vulnerability reduction and resilience building. The focus of the SI is the impact of risk information, communication and representation, risk knowledge as related to science and practice, risk perception and awareness, and risk culture on multi-faceted vulnerability and several aspects of resilience

Linking Textual Resources to Support Information Discovery

A vast amount of information is today stored in the form of textual documents, many of which are available online. These documents come from different sources and are of different types. They include newspaper articles, books, corporate reports, encyclopedia entries and research papers. At a semantic level, these documents contain knowledge, which was created by explicitly connecting information and expressing it in the form of a natural language. However, a significant amount of knowledge is not explicitly stated in a single document, yet can be derived or discovered by researching, i.e. accessing, comparing, contrasting and analysing, information from multiple documents. Carrying out this work using traditional search interfaces is tedious due to information overload and the difficulty of formulating queries that would help us to discover information we are not aware of. In order to support this exploratory process, we need to be able to effectively navigate between related pieces of information across documents. While information can be connected using manually curated cross-document links, this approach not only does not scale, but cannot systematically assist us in the discovery of sometimes non-obvious (hidden) relationships. Consequently, there is a need for automatic approaches to link discovery. This work studies how people link content, investigates the properties of different link types, presents new methods for automatic link discovery and designs a system in which link discovery is applied on a collection of millions of documents to improve access to public knowledge

Geological and Mineralogical Sequestration of CO2

The rapid increasing of concentrations of anthropologically generated greenhouse gases (primarily CO2) in the atmosphere is responsible for global warming and ocean acidification. The International Panel on Climate Change (IPCC) indicates that carbon capture and storage (CCS) techniques are a necessary measure to reduce greenhouse gas emissions in the short-to-medium term. One of the technological solutions is the long-term storage of CO2 in appropriate geological formations, such as deep saline formations and depleted oil and gas reservoirs. Promising alternative options that guarantee the permanent capture of CO2, although on a smaller scale, are the in-situ and ex-situ fixation of CO2 in the form of inorganic carbonates via the carbonation of mafic and ultramafic rocks and of Mg/Ca-rich fly ash, iron and steel slags, cement waste, and mine tailings. According to this general framework, this Special Issue collects articles covering various aspects of recent scientific advances in the geological and mineralogical sequestration of CO2. In particular, it includes the assessment of the storage potential of candidate injection sites in Croatia, Greece, and Norway; numerical modelling of geochemical–mineralogical reactions and CO2 flow; studies of natural analogues providing information on the processes and the physical–chemical conditions characterizing serpentinite carbonation; and experimental investigations to better understand the effectiveness and mechanisms of geological and mineralogical CO2 sequestration

Internet of Things. Information Processing in an Increasingly Connected World

This open access book constitutes the refereed post-conference proceedings of the First IFIP International Cross-Domain Conference on Internet of Things, IFIPIoT 2018, held at the 24th IFIP World Computer Congress, WCC 2018, in Poznan, Poland, in September 2018. The 12 full papers presented were carefully reviewed and selected from 24 submissions. Also included in this volume are 4 WCC 2018 plenary contributions, an invited talk and a position paper from the IFIP domain committee on IoT. The papers cover a wide range of topics from a technology to a business perspective and include among others hardware, software and management aspects, process innovation, privacy, power consumption, architecture, applications