O modelo de recuperação de informação mais amplamente utilizado no contexto de acervos digitais é o Vector Space Model. Algoritmos implementados para este modelo que aproveitam informações sobre relevância obtidas dos usuários (chamados feedbacks) na tentativa de melhorar os resultados da busca. Porém, estes algoritmos de feedback de relevância não possuem uma estratégia global e permanente, as informações obtidas desses feedbacks são descartadas para cada nova sessão de usuário (são perenes) ou não modificam os documentos como um todo (são alterações locais). Este trabalho apresenta um método de feedbacks de relevância denominado orientado a termos, permitindo que as modificações realizadas por influência dos feedbacks dos usuários sejam globais e permanentes. Foram realizados experimentos utilizando o dataset ClueWeb09 que dão evidências de que este método melhora a qualidade dos resultados da busca em relação ao modelo tradicional Vector Space Model. / The Vector Space Model is the most widely used information retrieval model within digital libraries\' systems. Algorithms developed to be used with this model use relevance information obtained from users (called feedbacks) to improve the search results. However, the relevance feedback algorithms developed are not global nor permanent, the feedbacks are discarded in users new sessions and do not affect every document. This paper presents a method that uses of relevance feedback named terms oriented. In this method, users\' feedbacks lead to modifications in the terms\' vectors representations. These modifications are global and permanent, influencing further searches. An experiment was conducted using the ClueWeb09 dataset, giving evidence that this method improves the quality of search results when compared with Vector Space Model.

A localização de páginas relevantes na Internet em atividades como clipping de notícias, detecção de uso indevido de marcas ou em serviços anti-phishing torna-se cada vez mais complexa devido a vários fatores como a quantidade cada vez maior de páginas na Web e a grande quantidade de páginas irrelevantes retornadas por mecanismos de busca. Em muitos casos as técnicas tradicionais utilizadas em mecanismos de busca na Internet, isto é, localização de termos em páginas e ordenação por relevância, não são suficientes para resolver o problema de localização de páginas específicas em atividades como as citadas anteriormente. A contextualização das páginas, ou seja, a classificação de páginas segundo um contexto definido pelo usuário baseando-se nas necessidades de uma atividade específica deve permitir uma busca mais eficiente por páginas na Internet. Neste trabalho é estudada a utilização de métodos de mineração na Web para a composição de métodos de contextualização de páginas, que permitam definir contextos mais sofisticados como seu assunto ou alguma forma de relacionamento. A contextualização de páginas deve permitir a solução de vários problemas na busca de páginas na Internet pela composição de métodos, que permitam a localização de páginas através de um conjunto de suas características, diferentemente de mecanismos de busca tradicionais que apenas localizam páginas que possuam um ou mais termos especificados. / Internet services as news clipping service, anti-phising, anti-plagiarism service and other that require intensive searching in Internet have a difficult work, because of huge number of existing pages. Search Engines try driver this problem, but search engines methods retrieve a lot of irrelevant pages, some times thousands of pages and more powerful methods are necessary to drive this problem. Page content, subject, hyperlinks or location can be used to define page context and create a more powerful method that can retrieve more relevant pages, improving precision. Classification of page context is defined as classification of a page by a set of its feature. This report presents a study about Web Mining, Search Engines and application of web mining technologies to classify page context. Page context classification applied to search engines must solve the problem of irrelevant pages flood by allowing search engines retrieve pages of a context.

Background. In the area of Geographic Information Systems (GIS), a shared discipline between informatics and geography, the term geo-parsing is used to describe the process of identifying names in text, which in computational linguistics is known as named entity recognition and classification (NERC). The term geo-coding is used for the task of mapping from implicitly geo-referenced datasets (such as structured address records) to explicitly geo-referenced representations (e.g., using latitude and longitude). However, present-day GIS systems provide no automatic geo-coding functionality for unstructured text. In Information Extraction (IE), processing of named entities in text has traditionally been seen as a two-step process comprising a flat text span recognition sub-task and an atomic classification sub-task; relating the text span to a model of the world has been ignored by evaluations such as MUC or ACE (Chinchor (1998); U.S. NIST (2003)). However, spatial and temporal expressions refer to events in space-time, and the grounding of events is a precondition for accurate reasoning. Thus, automatic grounding can improve many applications such as automatic map drawing (e.g. for choosing a focus) and question answering (e.g. for questions like How far is London from Edinburgh?, given a story in which both occur and can be resolved). Whereas temporal grounding has received considerable attention in the recent past (Mani and Wilson (2000); Setzer (2001)), robust spatial grounding has long been neglected. Concentrating on geographic names for populated places, I define the task of automatic Toponym Resolution (TR) as computing the mapping from occurrences of names for places as found in a text to a representation of the extensional semantics of the location referred to (its referent), such as a geographic latitude/longitude footprint. The task of mapping from names to locations is hard due to insufficient and noisy databases, and a large degree of ambiguity: common words need to be distinguished from proper names (geo/non-geo ambiguity), and the mapping between names and locations is ambiguous (London can refer to the capital of the UK or to London, Ontario, Canada, or to about forty other Londons on earth). In addition, names of places and the boundaries referred to change over time, and databases are incomplete. Objective. I investigate how referentially ambiguous spatial named entities can be grounded, or resolved, with respect to an extensional coordinate model robustly on open-domain news text. I begin by comparing the few algorithms proposed in the literature, and, comparing semiformal, reconstructed descriptions of them, I factor out a shared repertoire of linguistic heuristics (e.g. rules, patterns) and extra-linguistic knowledge sources (e.g. population sizes). I then investigate how to combine these sources of evidence to obtain a superior method. I also investigate the noise effect introduced by the named entity tagging step that toponym resolution relies on in a sequential system pipeline architecture. Scope. In this thesis, I investigate a present-day snapshot of terrestrial geography as represented in the gazetteer defined and, accordingly, a collection of present-day news text. I limit the investigation to populated places; geo-coding of artifact names (e.g. airports or bridges), compositional geographic descriptions (e.g. 40 miles SW of London, near Berlin), for instance, is not attempted. Historic change is a major factor affecting gazetteer construction and ultimately toponym resolution. However, this is beyond the scope of this thesis. Method. While a small number of previous attempts have been made to solve the toponym resolution problem, these were either not evaluated, or evaluation was done by manual inspection of system output instead of curating a reusable reference corpus. Since the relevant literature is scattered across several disciplines (GIS, digital libraries, information retrieval, natural language processing) and descriptions of algorithms are mostly given in informal prose, I attempt to systematically describe them and aim at a reconstruction in a uniform, semi-formal pseudo-code notation for easier re-implementation. A systematic comparison leads to an inventory of heuristics and other sources of evidence. In order to carry out a comparative evaluation procedure, an evaluation resource is required. Unfortunately, to date no gold standard has been curated in the research community. To this end, a reference gazetteer and an associated novel reference corpus with human-labeled referent annotation are created. These are subsequently used to benchmark a selection of the reconstructed algorithms and a novel re-combination of the heuristics catalogued in the inventory. I then compare the performance of the same TR algorithms under three different conditions, namely applying it to the (i) output of human named entity annotation, (ii) automatic annotation using an existing Maximum Entropy sequence tagging model, and (iii) a na¨ıve toponym lookup procedure in a gazetteer. Evaluation. The algorithms implemented in this thesis are evaluated in an intrinsic or component evaluation. To this end, we define a task-specific matching criterion to be used with traditional Precision (P) and Recall (R) evaluation metrics. This matching criterion is lenient with respect to numerical gazetteer imprecision in situations where one toponym instance is marked up with different gazetteer entries in the gold standard and the test set, respectively, but where these refer to the same candidate referent, caused by multiple near-duplicate entries in the reference gazetteer. Main Contributions. The major contributions of this thesis are as follows: • A new reference corpus in which instances of location named entities have been manually annotated with spatial grounding information for populated places, and an associated reference gazetteer, from which the assigned candidate referents are chosen. This reference gazetteer provides numerical latitude/longitude coordinates (such as 51320 North, 0 50 West) as well as hierarchical path descriptions (such as London > UK) with respect to a world wide-coverage, geographic taxonomy constructed by combining several large, but noisy gazetteers. This corpus contains news stories and comprises two sub-corpora, a subset of the REUTERS RCV1 news corpus used for the CoNLL shared task (Tjong Kim Sang and De Meulder (2003)), and a subset of the Fourth Message Understanding Contest (MUC-4; Chinchor (1995)), both available pre-annotated with gold-standard. This corpus will be made available as a reference evaluation resource; • a new method and implemented system to resolve toponyms that is capable of robustly processing unseen text (open-domain online newswire text) and grounding toponym instances in an extensional model using longitude and latitude coordinates and hierarchical path descriptions, using internal (textual) and external (gazetteer) evidence; • an empirical analysis of the relative utility of various heuristic biases and other sources of evidence with respect to the toponym resolution task when analysing free news genre text; • a comparison between a replicated method as described in the literature, which functions as a baseline, and a novel algorithm based on minimality heuristics; and • several exemplary prototypical applications to show how the resulting toponym resolution methods can be used to create visual surrogates for news stories, a geographic exploration tool for news browsing, geographically-aware document retrieval and to answer spatial questions (How far...?) in an open-domain question answering system. These applications only have demonstrative character, as a thorough quantitative, task-based (extrinsic) evaluation of the utility of automatic toponym resolution is beyond the scope of this thesis and left for future work.

Depuis l'explosion du Web, la Recherche d'Information (RI) s'est vue étendue et les moteurs de recherche sur le Web ont vu le jour. Les méthodes classiques de la RI, surtout destinées à des recherches textuelles simples, se sont retrouvées face à des documents de différents formats et des contenus riches. L'utilisateur, en réponse à cette avancée, est devenu plus exigeant quant aux résultats retournés par les systèmes de RI. La personnalisation tente de répondre à ces exigences en ayant pour objectif principal l'amélioration des résultats retournés à l'utilisateur en fonction de sa perception et de ses intérêts ainsi que de ses préférences. Le présent travail de thèse se situe à la croisée des différents aspects présentés et couvre cette problématique. Elle a pour objectif principal de proposer des solutions nouvelles et efficaces à cette problématique. Pour atteindre cet objectif, un système de personnalisation de la recherche spatiale et sémantique sur le Web et intégrant la modélisation de l'utilisateur, a été proposé. Ce système comprend deux volets : 1/ la modélisation de l'utilisateur ; 2/ la collaboration implicite des utilisateurs à travers la construction d'un réseau de modèles utilisateurs, construit itérativement lors des différentes recherches effectuées en ligne. Un prototype supportant le système proposé a été développé afin d'expérimenter et d'évaluer l'ensemble de la proposition. Ainsi, nous avons effectué un ensemble d'évaluation, dont les principales sont : a) l'évaluation de la qualité du modèle de l'utilisateur ; b) l'évaluation de l'efficacité de la recherche d'information ; c) l’évaluation de l'efficacité de la recherche d'information intégrant les informations spatiales ; d) l'évaluation de la recherche exploitant le réseau d'utilisateurs. Les expérimentations menées montrent une amélioration de la personnalisation des résultats présentés par rapport à ceux obtenus par d'autres moteurs de recherche. / The web explosion has led Information Retrieval (IR) to be extended and web search engines emergence. The conventional IR methods, usually intended for simple textual searches, faced new documents types and rich and scalable contents. The users, facing these evolutions, ask more for IR systems search results quality. In this context, the personalization main objective is improving results returned to the end user based sing on its perception and its interests and preferences. This thesis context is concerned with these different aspects. Its main objective is to propose new and effective solutions to the personalization problem. To achieve this goal, a spatial and semantic web personalization system integrating implicit user modeling is proposed. This system has two components: 1/ user modeling; /2 implicit users' collaboration through the construction of a users' models network. A system prototype was developed for the evaluation purpose that contains: a) user model quality evaluation; b) information retrieval quality evaluation; c) information retrieval quality evaluation with the spatial user model data; d) information retrieval quality evaluation with the whole user model data and the users' models network. Experiments showed amelioration in the personalized search results compared to a baseline web search.

Web Information Extraction (WIE) is the discipline dealing with the discovery, processing and extraction of specific pieces of information from semi-structured or unstructured web pages. The World Wide Web comprises billions of web pages and there is much need for systems that will locate, extract and integrate the acquired knowledge into organisations practices. There are some commercial, automated web extraction software packages, however their success comes from heavily involving their users in the process of finding the relevant web pages, preparing the system to recognise items of interest on these pages and manually dealing with the evaluation and storage of the extracted results. This research has explored WIE, specifically with regard to the automation of the extraction and validation of online training information. The work also includes research and development in the area of automated Web Information Retrieval (WIR), more specifically in Web Searching (or Crawling) and Web Classification. Different technologies were considered, however after much consideration, Naïve Bayes Networks were chosen as the most suitable for the development of the classification system. The extraction part of the system used Genetic Programming (GP) for the generation of web extraction solutions. Specifically, GP was used to evolve Regular Expressions, which were then used to extract specific training course information from the web such as: course names, prices, dates and locations. The experimental results indicate that all three aspects of this research perform very well, with the Web Crawler outperforming existing crawling systems, the Web Classifier performing with an accuracy of over 95% and a precision of over 98%, and the Web Extractor achieving an accuracy of over 94% for the extraction of course titles and an accuracy of just under 67% for the extraction of other course attributes such as dates, prices and locations. Furthermore, the overall work is of great significance to the sponsoring company, as it simplifies and improves the existing time-consuming, labour-intensive and error-prone manual techniques, as will be discussed in this thesis. The prototype developed in this research works in the background and requires very little, often no, human assistance.

Ding, Ling. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves [43]-45). / Abstract also in Chinese. / Thesis Committee --- p.i / Abstract --- p.ii / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Background --- p.1 / Chapter 1.2 --- Motivation --- p.3 / Chapter 1.3 --- Thesis Organization --- p.4 / Chapter 2 --- Representative Skylines and Basic Properties --- p.6 / Chapter 2.1 --- Existing Formulation --- p.6 / Chapter 2.1.1 --- Max-dominance Representative Skyline --- p.6 / Chapter 2.1.2 --- Defects of the Existing Formulation --- p.7 / Chapter 2.2 --- Our Formulation --- p.9 / Chapter 2.2.1 --- Distance-based Representative Skyline --- p.9 / Chapter 2.2.2 --- Properties of Our Formulation --- p.10 / Chapter 2.3 --- Problem Definition --- p.12 / Chapter 3 --- The Two-dimensional Case --- p.13 / Chapter 3.1 --- Algorithm 2D-opt --- p.13 / Chapter 3.2 --- Time Complexity --- p.15 / Chapter 3.3 --- Computing Covering Circles --- p.15 / Chapter 4 --- The Higher-dimensional Case --- p.18 / Chapter 4.1 --- NP-hardness and 2-approximation --- p.18 / Chapter 4.1.1 --- Proof of NP-hardness --- p.18 / Chapter 4.1.2 --- Algorithm naive-greedy --- p.19 / Chapter 4.2 --- Algorithm I-greedy --- p.20 / Chapter 4.2.1 --- Conservative Skyline --- p.22 / Chapter 4.2.2 --- Access Order --- p.23 / Chapter 4.3 --- Computing the Maximum Representative Distance --- p.27 / Chapter 5 --- Experiments --- p.30 / Chapter 5.1 --- Data --- p.30 / Chapter 5.2 --- Representation Quality --- p.31 / Chapter 5.2.1 --- Representative Skylines --- p.31 / Chapter 5.2.2 --- Representation Error Comparison --- p.33 / Chapter 5.3 --- Efficiency --- p.34 / Chapter 5.3.1 --- Running Time Comparison --- p.34 / Chapter 5.3.2 --- Scalability Comparison --- p.37 / Chapter 6 --- Related Work --- p.39 / Chapter 7 --- Conclusions --- p.41 / A List of Publications --- p.42 / Bibliography --- p.43

Chen, Wenhao. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (p. 63-70). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Ontologies and Folksonomies --- p.1 / Chapter 1.2 --- Motivation --- p.3 / Chapter 1.2.1 --- Semantics in Folksonomies --- p.3 / Chapter 1.2.2 --- Ontologies with basic level concepts --- p.5 / Chapter 1.2.3 --- Context and Context Effect --- p.6 / Chapter 1.3 --- Contributions --- p.6 / Chapter 1.4 --- Structure of the Thesis --- p.8 / Chapter 2 --- Background Study --- p.10 / Chapter 2.1 --- Semantic Web --- p.10 / Chapter 2.2 --- Ontology --- p.12 / Chapter 2.3 --- Folksonomy --- p.14 / Chapter 2.4 --- Cognitive Psychology --- p.17 / Chapter 2.4.1 --- Category (Concept) --- p.17 / Chapter 2.4.2 --- Basic Level Categories (Concepts) --- p.17 / Chapter 2.4.3 --- Context and Context Effect --- p.20 / Chapter 2.5 --- F1 Evaluation Metric --- p.21 / Chapter 2.6 --- State of the Art --- p.23 / Chapter 2.6.1 --- Ontology Learning --- p.23 / Chapter 2.6.2 --- Semantics in Folksonomy --- p.26 / Chapter 3 --- Ontology Learning from Folksonomies --- p.28 / Chapter 3.1 --- Generating Ontologies with Basic Level Concepts from Folksonomies --- p.29 / Chapter 3.1.1 --- Modeling Instances and Concepts in Folksonomies --- p.29 / Chapter 3.1.2 --- The Metric of Basic Level Categories (Concepts) --- p.30 / Chapter 3.1.3 --- Basic Level Concepts Detection Algorithm --- p.31 / Chapter 3.1.4 --- Ontology Generation Algorithm --- p.34 / Chapter 3.2 --- Evaluation --- p.35 / Chapter 3.2.1 --- Data Set and Experiment Setup --- p.35 / Chapter 3.2.2 --- Quantitative Analysis --- p.36 / Chapter 3.2.3 --- Qualitative Analysis --- p.39 / Chapter 4 --- Context Effect on Ontology Learning from Folksonomies --- p.43 / Chapter 4.1 --- Context-aware Basic Level Concepts Detection --- p.44 / Chapter 4.1.1 --- Modeling Context in Folksonomies --- p.44 / Chapter 4.1.2 --- Context Effect on Category Utility --- p.45 / Chapter 4.1.3 --- Context-aware Basic Level Concepts Detection Algorithm --- p.46 / Chapter 4.2 --- Evaluation --- p.47 / Chapter 4.2.1 --- Data Set and Experiment Setup --- p.47 / Chapter 4.2.2 --- Result Analysis --- p.49 / Chapter 5 --- Potential Applications --- p.54 / Chapter 5.1 --- Categorization of Web Resources --- p.54 / Chapter 5.2 --- Applications of Ontologies --- p.55 / Chapter 6 --- Conclusion and Future Work --- p.57 / Chapter 6.1 --- Conclusion --- p.57 / Chapter 6.2 --- Future Work --- p.59 / Bibliography --- p.63

隨著互聯網上3D模型的大量增加，產生了開發3D模型搜索引擎的需求。本論文提出了一個基於草圖和3D模型的3D模型搜索引擎。 / 對於使用3D模型作檢索條件的搜索系統，我們提出了兩種新的3D模型描述子，分別叫做Sphere Image 描述子和Bag-of-View-Words (BoVW)描述子。Sphere Image描述子是由一系列投影圖的特徵組成。我們將每一個視角看到的圖形都當作是一個"像素"，把視角的位置看作像素點的位置，把所看到的圖形的特徵值看作是像素值。我們同時也提出了一種基於概率圖的3D模型匹配算法，並開發了一個3D模型檢索系統來檢測我們的算法。BoVW描述子通過3D模型投影圖出現的次數來描述3D模型。我們用一種自適應的聚類算法，對3D模型的所有投影圖進行分類，然後用一個多層次的柱狀圖來描述一個3D模型。我們同時提出一種新的金字塔匹配算法來比較3D模型。我們使用SHREC和普林斯頓的3D模型庫來檢驗我們的系統，實驗結果證明我們的系統在檢索效率和精度上都優與現今的3D模型檢索系統。 / 對於使用草圖作檢索條件的3D模型搜索系統，我們提出Bigger ExposureOpportunity Views (BEOV) 描述子來表示3D模型，同時提出Shape-Ring描述子來表示草圖。BEOV描述子是由一些特徵圖組成，這些圖的特點是更容易被人們看到。Shape-Ring描述子保留了圖形的輪廓和內部特徵。我們使用SHREC2012草圖數據庫來檢驗我們的系統，實驗結果證明我們的系統在精度和計算複雜度上都優與現今的3D模型檢索系統。 / The large number of 3D models on the Internet encourages us to develop 3D model search engines. In this dissertation, we present a 3D model retrieval system using both the 3D model query and the sketch query. / For 3D model query based retrieval system, we propose two new 3D model descriptors, named the Sphere Image and the Bag-of-View-Words (BoVW) descriptor. The Sphere Image is defined as a collection of view features. A viewpoint of a 3D model is regarded as a "pixel": (1) The position of the viewpoint is denoted as the coordinate of the "pixel". (2) The feature descriptor of the projected view is denoted as the value of the "pixel". We also propose a probabilistic graphical model for 3D model matching, and develop a 3D model retrieval system to test our approach. The BoVW descriptor describes a 3D model by measuring the occurrences of its projected views. An adaptive clustering method is applied to reduce the redundancy of the projected views of each 3D model. A 3D model is represented by a multi-resolution histogram, which is combined by several BoVW descriptors at different levels. The codebook is obtained by unsupervised learning. We also propose a new pyramid matching method for 3D model comparison. We have conducted experiments based on the SHape REtrieval Contest (SHREC) 2012 Generic 3D model benchmark and the Princeton Shape Benchmark (PSB). Experimental results indicate that our system outperforms some state-of-the-art 3D model retrieval systems with respect to the retrieval precision and the computational cost. / For sketch query based retrieval system, we propose a Bigger Exposure Opportunity Views (BEOV) descriptor and a Shape-Ring descriptor, for representing the 3D model candidates and the sketch query, respectively. The BEOV descriptor represents a 3D model by several characteristic views, which have more chances to be exposed to people. The Shape-Ring descriptor preserves the features of the contour and the inside detail of the sketch query and the BEOV. Experiments have been conducted based on the SHape REtrieval Contest (SHREC) 2012 and SHREC 2013 sketch track data sets. Our approach outperforms the existing 3D model retrieval methods in terms of the retrieval precision and the computational cost. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Ding, Ke. / Thesis (Ph.D.) Chinese University of Hong Kong, 2014. / Includes bibliographical references (leaves 107-120). / Abstracts also in Chinese.

Devido ao estabelecimento de negócios pela Internet, o Google alcançou notoriedade mundial, tornando-se atrativo às empresas como canal do Marketing Digital na utilização da ferramenta Google Adwords. Em vista disso, o presente estudo consistiu no levantamento bibliográfico do Marketing de Busca e da Biblioteconomia e Documentação, no qual o principal objetivo é contribuir através do uso de técnicas de Indexação, no processo de seleção de palavras-chave, e conduzi-las na ferramenta de anúncios do Google. Os métodos desta pesquisa foram estabelecidos pela Representação Documentária, com a finalidade de contribuir na diminuição de palavras-chave que oneram as campanhas no Adwords. A partir da coleta dos assuntos mais acessados no Google Trends, no período de quatro meses (jan-abr) de 2017, e a realização de testes em janeiro de 2018 no planejador de palavras-chave do Google, apresentamos a avaliação dos resultados comparativos entre os dados coletados e os dados da lista, com a finalidade de responder se o uso das técnicas de indexação podem ser ou não favoráveis nas criações de campanhas aos clientes brasileiros neste mecanismo de busca. Concluiu-se que a contribuição da Indexação é favorável as campanhas publicitárias no Google, e também requer a inclusão do bibliotecário, já que se trata do profissional com habilidades e competências necessárias na execução desta tarefa, que ficará atento as influências exercidas pelos algoritmos tanto nos valores de palavras-chave quanto na recuperação desses termos ao público de interesse no mecanismo de busca. / Due to the establishment of Internet business, Google has achieved world renown, becoming attractive to companies as a channel of Digital Marketing in the use of Google Adwords tool. Therefore, the present study consisted of a bibliographical survey of Search Marketing and Librarianship and Documentation, in which the main objective is to contribute using Indexing techniques, in the process of selection of keywords, and to conduct them in the Google Ad Tool. The methods of this research were established by the Documentary Representation, with the purpose of contributing to the reduction of keywords that affect the campaigns in Adwords. From the most commonly accessed subjects in Google Trends in the four-month period (Jan-Apr), 2017, and testing in January 2018 on Google\'s keyword planner, we present an assessment of the comparative results between the collected data and the data of the list, in order to answer if the use of the indexing techniques can be or not favorable in the creations of campaigns to the Brazilian clients in this search engine. It was concluded that the contribution of Indexation is favorable to advertising campaigns in Google, and also requires the inclusion of the librarian, since it is the professional with the necessary skills and competences in the execution of this task, which will be attentive to the influences exerted by the algorithms both in keyword values as well as the retrieval of those terms to the public of interest in the search engine.

This dissertation explores three research topics related to automated spatiotemporal and semantic information extraction about hazard events from Web news reports and other social media. The dissertation makes a unique contribution of bridging geographic information science, geographic information retrieval, and natural language processing. Geographic information retrieval and natural language processing techniques are applied to extract spatiotemporal and semantic information automatically from Web documents, to retrieve information about patterns of hazard events that are not explicitly described in the texts. Chapters 2, 3 and 4 can be regarded as three standalone journal papers. The research topics covered by the three chapters are related to each other, and are presented in a sequential way. Chapter 2 begins with an investigation of methods for automatically extracting spatial and temporal information about hazards from Web news reports. A set of rules is developed to combine the spatial and temporal information contained in the reports based on how this information is presented in text in order to capture the dynamics of hazard events (e.g., changes in event locations, new events occurring) as they occur over space and time. Chapter 3 presents an approach for retrieving semantic information about hazard events using ontologies and semantic gazetteers. With this work, information on the different kinds of events (e.g., impact, response, or recovery events) can be extracted as well as information about hazard events at different levels of detail. Using the methods presented in Chapter 2 and 3, an approach for automatically extracting spatial, temporal, and semantic information from tweets is discussed in Chapter 4. Four different elements of tweets are used for assigning appropriate spatial and temporal information to hazard events in tweets. Since tweets represent shorter, but more current information about hazards and how they are impacting a local area, key information about hazards can be retrieved through extracted spatiotemporal and semantic information from tweets.