In book search, relevant book information should be returned in response to a query. Books contain complex, multi-faceted information such as metadata, outlines, and main text, where the outline provides hierarchical information between chapters and sections. Generative retrieval (GR) is a new retrieval paradigm that consolidates corpus information into a single model to generate identifiers of documents that are relevant to a given query. How can GR be applied to book search? Directly applying GR to book search is a challenge due to the unique characteristics of book search: The model needs to retain the complex, multi-faceted information of the book, which increases the demand for labeled data. Splitting book information and treating it as a collection of separate segments for learning might result in a loss of hierarchical information. We propose an effective Generative retrieval framework for Book Search (GBS) that features two main components: data augmentation and outline-oriented book encoding. For data augmentation, GBS constructs multiple query-book pairs for training; it constructs multiple book identifiers based on the outline, various forms of book contents, and simulat
Scholars, awards committees, and laypeople frequently discuss the merit of written works. Literary professionals and journalists differ in how much perspectivism they concede in their book reviews. Here, we quantify how strongly book reviews are determined by the actual book contents vs. idiosyncratic reader tendencies. In our analysis of 624,320 numerical and textual book reviews, we find that the contents of professionally published books are not predictive of a random reader's reading enjoyment. Online reviews of popular fiction and non-fiction books carry up to ten times more information about the reviewer than about the book. For books of a preferred genre, readers might be less likely to give low ratings, but still struggle to converge in their relative assessments. We find that book evaluations generalize more across experienced review writers than casual readers. When discussing specific issues with a book, one review text had poor predictability of issues brought up in another review of the same book. We conclude that extreme perspectivism is a justifiable position when researching literary quality, bestowing literary awards, and designing recommendation systems.
Finding enjoyable fiction books can be challenging, partly because stories are multi-faceted and one's own literary taste might be difficult to ascertain. Here, we introduce the ISAAC method (Introspection-Support, AI-Annotation, and Curation), a pipeline which supports fiction readers in gaining awareness of their literary preferences and finding enjoyable books. ISAAC consists of four steps: a user supplies book ratings, an AI agent researches and annotates the provided books, patterns in book enjoyment are reviewed by the user, and the AI agent recommends new books. In this proof-of-concept self-study, the authors test whether ISAAC can highlight idiosyncratic patterns in their book enjoyment, spark a deeper reflection about their literary tastes, and make accurate, personalized recommendations of enjoyable books and underexplored literary niches. Results highlight substantial advantages of ISAAC over existing methods such as an integration of automation and intuition, accurate and customizable annotations, and explainable book recommendations. Observed disadvantages are that ISAAC's outputs can elicit false self-narratives (if statistical patterns are taken at face value), that
Inspired by the recent 90th anniversary of the Scottish Book we present some reflections about its impact. First we discuss new areas of mathematics it helped launch. Then we argue that it was actively used in stimulating the interests and results of junior mathematicians and students. Also, we summarize the progress during the decade that has passed since the publication of [55], which contained a review of solved problems from the Scottish Book. We also provide an overview of collections of open problems related in one way or another to the Scottish Book. All formulations of the Scottish Book problems in English are cited here from Mauldin, Richard Daniel (ed.) 2015: The Scottish Book. Mathematics from the Scottish Café. With selected problems from the New Scottish Book. 2nd updated and enlarged edition. Cham: Birkhäuser/Springer
We build handle decompositions of n-manifolds that encode given open book decompositions and describe handle slides that reveal new open book decompositions on the same underlying manifold, for $n \geq 3$. This recovers known stabilization operations for open books. As an application, we show that any open book with trivial monodromy can be stabilized to an open book whose page is a boundary connected sum of trivial disk bundles over spheres.
The cover is the face of a book and is a point of attraction for the readers. Designing book covers is an essential task in the publishing industry. One of the main challenges in creating a book cover is representing the theme of the book's content in a single image. In this research, we explore ways to produce a book cover using artificial intelligence based on the fact that there exists a relationship between the summary of the book and its cover. Our key motivation is the application of text-to-image synthesis methods to generate images from given text or captions. We explore several existing text-to-image conversion techniques for this purpose and propose an approach to exploit these frameworks for producing book covers from provided summaries. We construct a dataset of English books that contains a large number of samples of summaries of existing books and their cover images. In this paper, we describe our approach to collecting, organizing, and pre-processing the dataset to use it for training models. We apply different text-to-image synthesis techniques to generate book covers from the summary and exhibit the results in this paper.
Conventional picture-book production imposes substantial physical and temporal demands on creators, often constraining opportunities for high-level artistic exploration. While generative AI can drastically accelerate image generation, concerns remain regarding style homogenization and the erosion of authorial agency in professional practice. This study presents an empirical evaluation of an AI-collaborative workflow through the full production of one professional 15-illustration picture-book title, and compares the process with a conventional hand-drawn pipeline by the same creator. Quantitatively, the proposed workflow reduces total production time by 85.2% (from 2,162.8 to 320.4 hours), with the largest substitution observed in early drafting stages. Qualitatively, however, the core contribution is the strategic reallocation of labor: time saved in mechanical rendering is reinvested into high-level Judgment (aesthetic selection, narrative direction, and cross-scene consistency decisions) and Completion (embodied manual retouching and integrative refinement). Notably, 235 hours were devoted to Completion, indicating that publication-quality outcomes still depend on sustained human
In 2011, Thomson-Reuters introduced the Book Citation Index (BKCI) as part of the Science Citation Index (SCI). The interface of the Web of Science version 5 enables users to search for both "Books" and "Book Chapters" as new categories. Books and book chapters, however, were always among the cited references, and book chapters have been included in the database since 2005. We explore the two categories with both BKCI and SCI, and in the sister social sciences (SoSCI) and the arts & humanities (A&HCI) databases. Book chapters in edited volumes can be highly cited. Books contain many citing references but are relatively less cited. This may find its origin in the slower circulation of books than of journal articles. It is possible to distinguish between monographs and edited volumes among the "Books" scientometrically. Monographs may be underrated in terms of citation impact or overrated using publication performance indicators because individual chapters are counted as contributions separately in terms of articles, reviews, and/or book chapters.
A "monkey book" is a book consisting of a random distribution of letters and blanks, where a group of letters surrounded by two blanks is defined as a word. We compare the statistics of the word distribution for a monkey book with the corresponding distribution for the general class of random books, where the latter are books for which the words are randomly distributed. It is shown that the word distribution statistics for the monkey book is different and quite distinct from a typical sampled book or real book. In particular the monkey book obeys Heaps' power law to an extraordinary good approximation, in contrast to the word distributions for sampled and real books, which deviate from Heaps' law in a characteristics way. The somewhat counter-intuitive conclusion is that a "monkey book" obeys Heaps' power law precisely because its word-frequency distribution is not a smooth power law, contrary to the expectation based on simple mathematical arguments that if one is a power law, so is the other.
In this study, book summaries and categories taken from book sites were classified using word embedding methods, natural language processing techniques and machine learning algorithms. In addition, one hot encoding, Word2Vec and Term Frequency - Inverse Document Frequency (TF-IDF) methods, which are frequently used word embedding methods were used in this study and their success was compared. Additionally, the combination table of the pre-processing methods used is shown and added to the table. Looking at the results, it was observed that Support Vector Machine, Naive Bayes and Logistic Regression Models and TF-IDF and One-Hot Encoder word embedding techniques gave more successful results for Turkish texts.
We introduce the notion of a nested open book, a submanifold equipped with an open book structure compatible with an ambient open book, and describe in detail the special case of a push-off of the binding of an open book. This enables us to explicitly describe a natural open book decomposition of a fibre connected sum of two open books along their bindings, provided they are diffeomorphic and admit an open book structure themselves. Furthermore, we apply the results to contact open books, showing that the natural open book structure of a contact fibre connected sum of two adapted open books along their contactomorphic bindings is again adapted to the resulting contact structure.
We discuss embedding of manifolds in the category of open books, contact manifolds and contact open books. We prove an open book version of the Haefliger--Hirsch embedding theorem by showing that every $k$-connected closed $n$-manifold ($n\geq 7$, $k < \frac{n-4}{2}$) admits an open book embedding in the trivial open book of $\mathbb{S}^{2n-k}$. We then prove that every closed manifold $M^{2n+1}$ that bounds an achiral Lefschetz fibration, admits open book embedding in the trivial open book of $\mathbb{S}^{2\lfloor\frac{3n}{2}\rfloor + 3}$. We also prove that every closed manifold $M^{2n+1}$ bounding an achiral Lefschetz fibration admits a contact structure that isocontact embeds in the standard contact structure on $\mathbb{R}^{2n+3}.$ Finally, we give various examples of contact open book embeddings of contact $(2n+1)$-manifolds in the trivial supporting open book of the standard contact structure on $\mathbb{S}^{4n+1}.$
The PRobe far-Infrared Mission for Astrophysics (PRIMA) mission concept is a proposed mission to NASA's Astrophysics Probe Explorer (APEX) call. The concept features a cryogenically cooled 1.8 m diameter telescope, and is designed to carry two science instruments covering the 24 to 264 $μ$m wavelength range: an imaging polarimeter (PRIMAger) and a spectrometer (FIRESS). The majority of PRIMA's time (75%) will be open to observations proposed by the community (General Observer science / GO), and all of data will be publicly available for archival research (Guest Investigator science / GI). Following up on the successful community engagement created by the first volume of the GO PRIMA Science Book (arXiv:2310.20572), Volume 2 gathers 120 new and updated contributed science cases which could be performed within the context of the PRIMA GO/GI program. This volume reflects the strong development of the community interest, awareness and involvement in PRIMA, and further develops how PRIMA's unprecedented capabilities can be leveraged for an impactful and innovative GO/GI program covering most areas of astrophysics and over 90% of the scientific questions and discovery areas in the Astro2
Information theoretical inequalities have strong ties with polymatroids and their representability. A polymatroid is entropic if its rank function is given by the Shannon entropy of the subsets of some discrete random variables. The book is a special iterated adhesive extension of a polymatroid with the property that entropic polymatroids have $n$-page book extensions over an arbitrary spine. We prove that every polymatroid has an $n$-page book extension over a single element and over an all-but-one-element spine. Consequently, for polymatroids on four elements, only book extensions over a two-element spine should be considered. F. Matúš proved that the Zhang-Yeung inequalities characterize polymatroids on four elements which have such a 2-page book extension. The $n$-page book inequalities, defined in this paper, are conjectured to characterize polymatroids on four elements which have $n$-page book extensions over a two-element spine. We prove that the condition is necessary; consequently every book inequality is an information inequality on four random variables. Using computer-aided multiobjective optimization, the sufficiency of the condition is verified up to 9-page book exten
In a book embedding of a graph G, the vertices of G are placed in order along a straight-line called spine of the book, and the edges of G are drawn on a set of half-planes, called the pages of the book, such that two edges drawn on a page do not cross each other. The minimum number of pages in which a graph can be embedded is called the book-thickness or the page-number of the graph. It is known that every planar graph has a book embedding on at most four pages. Here we investigate the book-embeddings of 1-planar graphs. A graph is 1-planar if it can be drawn in the plane such that each edge is crossed at most once. We prove that every 1-planar graph has a book embedding on at most 16 pages and every 3-connected 1-planar graph has a book embedding on at most 12 pages. The drawings can be computed in linear time from any given 1-planar embedding of the graph.
An open book decomposition of a 3-manifold $M$ induces a Heegaard splitting for $M$, and the minimal genus among all Heegaard splittings induced by open book decompositions is called the \emph{open book genus} of $M$. It is conjectured by Ozbagci \cite{O} that the open book genus is additive under the connected sum of 3-manifolds. In this paper, we prove that a non-prime 3-manifold which has open book genus 2 is homeomorphic to $L(p,1)\#L(q,1)$ for some integers $p,q eq\pm1$, that is, it has non-trivial prime pieces of open book genus 1. In particular, there cannot be a counter-example to additivity of the open book genus such that the connected sum has open book genus 2.
A $k$-page book drawing of a graph $G=(V,E)$ consists of a linear ordering of its vertices along a spine and an assignment of each edge to one of the $k$ pages, which are half-planes bounded by the spine. In a book drawing, two edges cross if and only if they are assigned to the same page and their vertices alternate along the spine. Crossing minimization in a $k$-page book drawing is NP-hard, yet book drawings have multiple applications in visualization and beyond. Therefore several heuristic book drawing algorithms exist, but there is no broader comparative study on their relative performance. In this paper, we propose a comprehensive benchmark set of challenging graph classes for book drawing algorithms and provide an extensive experimental study of the performance of existing book drawing algorithms.
The absence of books and book chapters in the Web of Science Citation Indexes (SCI, SSCI and A&HCI) has always been considered an important flaw but the Thomson Reuters 'Book Citation Index' database was finally available in October of 2010 indexing 29,618 books and 379,082 book chapters. The Book Citation Index opens a new window of opportunities for analyzing these fields from a bibliometric point of view. The main objective of this article is to analyze different impact indicators referred to the scientific publishers included in the Book Citation Index for the Social Sciences and Humanities fields during 2006-2011. This way we construct what we have called the 'Book Publishers Citation Reports'. For this, we present a total of 19 rankings according to the different disciplines in Humanities & Arts and Social Sciences & Law with six indicators for scientific publishers
This paper presents a first approach to analyzing the factors that determine the citation characteristics of books. For this we use the Thomson Reuters' Book Citation Index, a novel multidisciplinary database launched in 2010 which offers bibliometric data of books. We analyze three possible factors which are considered to affect the citation impact of books: the presence of editors, the inclusion in series and the type of publisher. Also, we focus on highly cited books to see if these factors may affect them as well. We considered as highly cited books, those in the top 5% of the most highly cited ones of the database. We define these three aspects and we present the results for four major scientific areas in order to identify field-based differences (Science, Engineering & Technology, Social Sciences and Arts & Humanities). Finally we conclude observing that differences were noted for edited books and types of publishers. Although books included in series showed higher impact in two areas.
In this paper we provide the reader with a visual representation of relationships among the impact of book chapters indexed in the Book Citation Index using information gain values and published by different academic publishers in specific disciplines. The impact of book chapters can be characterized statistically by citations histograms. For instance, we can compute the probability of occurrence of book chapters with a number of citations in different intervals for each academic publisher. We predict the similarity between two citation histograms based on the amount of relative information between such characterizations. We observe that the citation patterns of book chapters follow a Lotkaian distribution. This paper describes the structure of the Book Citation Index using 'heliocentric clockwise maps' which allow the reader not only to determine the grade of similarity of a given academic publisher indexed in the Book Citation Index with a specific discipline according to their citation distribution, but also to easily observe the general structure of a discipline, identifying the publishers with higher impact and output.