| { |
| "paper_id": "W14-0147", |
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| "date_generated": "2023-01-19T05:49:50.714892Z" |
| }, |
| "title": "IndoWordnet Visualizer: A Graphical User Interface for Browsing and Exploring Wordnets of Indian Languages", |
| "authors": [ |
| { |
| "first": "Devendra", |
| "middle": [], |
| "last": "Singh", |
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| "affiliation": { |
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| "institution": "IIT Bombay", |
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| "postCode": "400076", |
| "settlement": "Powai, Mumbai" |
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| }, |
| { |
| "first": "Chaplot", |
| "middle": [], |
| "last": "Sudha", |
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| "institution": "IIT Bombay", |
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| }, |
| "email": "chaplot@cse.iitb.ac.in" |
| }, |
| { |
| "first": "Bhingardive", |
| "middle": [], |
| "last": "Pushpak Bhattacharyya", |
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| "institution": "IIT Bombay", |
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| "abstract": "In this paper, we are presenting a graphical user interface to browse and explore the In-doWordnet lexical database for various Indian languages. IndoWordnet visualizer extracts the related concepts for a given word and displays a sub graph containing those concepts. The interface is enhanced with different features in order to provide flexibility to the user. IndoWordnet visualizer is made publically available. Though it was initially constructed for making the wordnet validation process easier, it is proving to be very useful in analyzing various Natural Language Processing tasks, viz.", |
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| "abstract": [ |
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| "text": "In this paper, we are presenting a graphical user interface to browse and explore the In-doWordnet lexical database for various Indian languages. IndoWordnet visualizer extracts the related concepts for a given word and displays a sub graph containing those concepts. The interface is enhanced with different features in order to provide flexibility to the user. IndoWordnet visualizer is made publically available. Though it was initially constructed for making the wordnet validation process easier, it is proving to be very useful in analyzing various Natural Language Processing tasks, viz.", |
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| "section": "Abstract", |
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| "text": "IndoWordnet (Bhattacharyya, 2010 ) is a linked lexical knowledge base consisting of wordnets of various Indian languages, where each wordnet is composed of synsets and semantic relations. This resource is very useful for various NLP applications viz., Machine Translation, Word Sense Disambiguation, Sentimental Analysis, Information Retrieval, etc. But to use this knowledge in an effective way, a set of tools are required to query, retrieve and visualize information from this knowledge base. Data visualization is the study of the visual representation of data, meaning \"information that has been abstracted in some schematic form, including attributes or variables for the units of information\" (Friendly, 2008) . The main goal of visualization is to organize information clearly and effectively through graphical means. We have developed a user interface that provides a graphical representation of In-doWordnet. Till date, no such tool was developed for visualizing the wordnet database for Indian languages. The visualizer we developed takes a word from a specific language as an input and displays the related concepts of that word depending upon its semantic and lexical relations with other words in the wordnet.", |
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| "start": 12, |
| "end": 32, |
| "text": "(Bhattacharyya, 2010", |
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| "text": "(Friendly, 2008)", |
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| "section": "Introduction", |
| "sec_num": "1" |
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| "text": "This paper is organized as follows. Section 2 covers a related work. Section 3 gives an overview of IndoWordnet. Section 4 describes In-doWordnet visualizer. Section 5 gives implementation details. Conclusion and future work are covered in Section 6.", |
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| "section": "Introduction", |
| "sec_num": "1" |
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| "text": "There are many wordnet visualizers available for browsing and exploring wordnets to better understand the concepts and semantic relations between them. Some of them include BabelNet explorer (Navigli, 2013) , AndreOrd (Johannsen and Pedersen, 2011) , Visuwords 1 , Nodebox 2 , Word-Ties (Pedersen et. al 2013) , WordVis (Vercruysse and Kuiper, 2011) etc. BabelNet explorer is designed for visualizing the lexical database BabelNet (Navigli and Ponzetto, 2012) . It uses the tree layout for visualization which allows intuitive navigation. It covers English, Italian, Catalan, Spanish, German and French languages. AndreOrd is the wordnet browser developed for the Danish wordnet, DanNet. It uses the open source framework Ruby on Rails and the graphing toolkit Protovis 3 . Visuwords is the online graphical dictionary designed for accessing Princeton WorNet (Fellbaum, 1998) . It uses a force-directed graph layout for visualizing the synset structure. Nodebox visualizer provides the static layout. It does not use any color or shape encoding in the graph. WordTies is the wordnet visualizer designed for Nordic and Baltic wordnets. It covers seven monolingual and four bilingual wordnets. It has been made available via META-SHARE 4 through the META-NORD project.", |
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| "text": "(Navigli, 2013)", |
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| "text": "(Johannsen and Pedersen, 2011)", |
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| "text": "(Pedersen et. al 2013)", |
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| "text": "(Navigli and Ponzetto, 2012)", |
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| "text": "(Fellbaum, 1998)", |
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| "section": "Related Work", |
| "sec_num": "2" |
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| "text": "IndoWordnet is the most useful multilingual lexical resource in Indian languages. Hindi wordnet is created manually using lexical knowledge from various dictionaries. Wordnets other than Hindi have been created by using expansion approach with Hindi as a pivot language. It includes 18 Indian languages 5 viz., Assamese,", |
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| "ref_spans": [], |
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| "section": "Overview of IndoWordnet", |
| "sec_num": "3" |
| }, |
| { |
| "text": "Bengali, Bodo, Gujarati, Kannada, Kashmiri, Nepali, Kashmiri, Konkani, Malayalam, Manipu- ri, Marathi, Nepali, Odiya, Punjabi, Sanskrit, Tamil, Telugu, Urdu, etc.", |
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| "section": "Overview of IndoWordnet", |
| "sec_num": "3" |
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| "text": "Expansion approach makes use of the fact that there are several 'universal concepts' which are independent of the language. If one language has synsets for universal concepts, then it makes sense to borrow this work for some other language. For such universal concepts, the semantic relations remain same across the languages. Hence one can directly borrow them for other languages. This principle is used in the creation of IndoWordnet. All the semantic relations for universal synsets are defined in Hindi and are borrowed by other languages. Expansion approach works very well for closely related languages like 'Hindi and Marathi'. The current statistics of the IndoWordnet is shown in Table 1 . IndoWordnet stores various relations among words and synsets. These relations give an important knowledge about the language structure. These are categorized under two labels viz., lexical relations and semantic relations.", |
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| "text": "Table 1", |
| "ref_id": "TABREF1" |
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| "section": "Overview of IndoWordnet", |
| "sec_num": "3" |
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| "text": "Lexical relations are present between the words. IndoWordnet contains different types of lexical relations listed below, \uf0b7 Gradation (state, size, light, gender, temperature, color, time, quality, action, manner) (for all parts-of-speech) IndoWordnet provides extra relations (Narayan et. al., 2002) in comparison with Princeton wordnet, e.g., gradation, causative form, nominal and verbal compounds, conjunction etc. All these relations are covered in IndoWordnet Visualizer. User can see these relations and understand them better visually. All these relations are used while finding the related concepts of a given word. The need to make entirely different explorer for In-doWordnet lies in its difference from other wordnets in terms of the structure and relations. The entirely different format makes it difficult to import other visualizers directly. Manually going through the wordnet relations takes very large time. Visualizer makes this process extremely efficient and intuitive. This motivated us to create a new visualizer for IndoWordnet. Developed GUI is enriched with various facilities as explained in Section 4.", |
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| "text": "(Narayan et. al., 2002)", |
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| "section": "Lexical Relations", |
| "sec_num": "3.1" |
| }, |
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| "text": "IndoWordnet visualizer is designed for visualizing the IndoWordnet database. It is made publically available on IndoWordnet website 6 . Related concepts of a given input word are extracted at different levels and a sub graph is displayed on a screen. The user interface layout and its features are described below.", |
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| "section": "IndoWordnet Visualizer", |
| "sec_num": "4" |
| }, |
| { |
| "text": "The interface of the visualizer consists of following I/O features.", |
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| "section": "User Interface Layout", |
| "sec_num": "4.1" |
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| "text": "\uf0b7 Text-box for the word to browse and explore http://www.cfilt.iitb.ac.in/indowordnet/ \uf0b7 Download option is provided for retrieving related words and concepts which can act as a good context clue for a given input word.", |
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| "section": "The input to the interface consists of:", |
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| }, |
| { |
| "text": "Interface is enhanced with the following features, which provide flexibility to the user to visualize the wordnet database.", |
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| "section": "Features", |
| "sec_num": "4.2" |
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| "text": "\uf0b7 Nodes are automatically arranged on the screen according to physics and depending on the total number of nodes. The repulsion between the nodes and the link distance is optimally calculated so as to display all nodes clearly. Here, nodes are nothing but the concepts from IndoWordnet. For a given input word, all related concepts are extracted from IndoWordnet and are displayed at appropriate positions on the screen.", |
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| "section": "Features", |
| "sec_num": "4.2" |
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| "text": "\uf0b7 The size of the node varies according to the number of its immediate neighbor. A node consisting large number of neighbors is bigger in size than a node with less number of neighbors. This highlights more frequent words against less frequent ones.", |
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| "section": "Features", |
| "sec_num": "4.2" |
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| "text": "\uf0b7 When a user moves a mouse pointer over a particular node, it highlights all its immediate neighbors along with that node. (Screenshot 6) \uf0b7 When a user moves a mouse pointer over a particular edge, it highlights the type of relation exist between the nodes. Different color encodings are used for displaying the lexical and semantic relations. (Screenshot 3) \uf0b7 User can click, drag, expand and fix nodes for better visibility. (Screenshot 4)", |
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| "start": 124, |
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| "text": "(Screenshot 6)", |
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| "text": "(Screenshot 3)", |
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| "sec_num": "4.2" |
| }, |
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| "text": "\uf0b7 Zoom in and zoom out facilities are also provided.", |
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| "section": "Features", |
| "sec_num": "4.2" |
| }, |
| { |
| "text": "\uf0b7 When a user clicks on a node all its semantic information is displayed on the screen. It includes synset id, synset words, gloss, and example sentence.", |
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| "section": "Features", |
| "sec_num": "4.2" |
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| "text": "\uf0b7 Download option is provided in order to get all the information displayed on a screen which is helpful for different NLP applications.", |
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| "section": "Features", |
| "sec_num": "4.2" |
| }, |
| { |
| "text": "In an interface, we provided two types of visual schemes. 1. By the number of levels 2. By the number of nodes", |
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| "section": "Visualization Schemes", |
| "sec_num": "4.3" |
| }, |
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| "text": "In the first scheme, for a given concept, related concepts are extracted according to different levels e.g., immediate neighbors, neighbors of immediate neighbors and so on. Sometimes due to large number of neighboring concepts user may face difficulty in visualization. For example, for the Hindi concept '\u092e\u093e\u0928\u0935\u0915 \u0943 \u0924\u093f' (man-made) given below, the number of extracted related concepts at different levels are shown in Table 2 .", |
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| "text": "Table 2", |
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| ], |
| "eq_spans": [], |
| "section": "Visualization Schemes", |
| "sec_num": "4.3" |
| }, |
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| "text": "As number of levels increases, number of nodes (related concepts) for the concept also increases drastically. It is very difficult to render such kind of concepts on a screen. That's why we provided a second visualization scheme in which user has been given a facility to choose number of nodes to be displayed on the screen (Screenshot 7). ", |
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| "section": "Visualization Schemes", |
| "sec_num": "4.3" |
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| "text": "The front-end of the IndoWordnet Visualizer uses Data Driven Documents (D3) JavaScript library, which allows us to present the data of nodes and edges from the back-end, graphically. This library allows us to define geometry for nodes and edges so as to automatically arrange them efficiently, while also allowing the user to click, drag and fix any node for better visibility. The library uses Scalable Vector Graphics (SVG), which allows us to zoom into the graph without pixelating the nodes, links or labels. The superiority of D3 lies in its support for dynamic behavior allowing user-friendly interaction and animation.", |
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| "section": "Implementation details", |
| "sec_num": "5" |
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| "text": "We have presented the IndoWordnet visualizer which can be used for browsing and exploring IndoWordnet lexical database. It is enhanced with various functionalities in order to provide flexibility to the user. It is very useful for wordnet validation process. It can be used in various Natural Language Processing applications viz., Word Sense Disambiguation, Information Retrieval, Semantic Relatedness etc. IndoWordnet visualizer is under development and some more features are yet to be included like generating the minimum sub graph between two given concepts.", |
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| "section": "Conclusion and Future Work", |
| "sec_num": "6" |
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| "text": "http://www.visuwords.com/ 2 http://nodebox.net/code/index.php/WordNet 3 http://vis.stanford.edu/protovis/", |
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| "text": "http://www.meta-share.org 5 Wordnets for Indian languages are developed in In-doWordNet project. Wordnets are available in following Indian languages: Assamese, Bodo, Bengali, English, Gujarati, Hindi, Kashmiri, Konkani, Kannada, Malayalam, Manipuri, Marathi, Nepali, Punjabi, Sanskrit, Tamil, Telugu and Urdu. These languages cover 3 different language families, Indo Aryan, Sino-Tebetian and Dravidian. http://www.cfilt.iitb.ac.in/indowordnet", |
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| "BIBREF0": { |
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| "title": "IndoWordnet", |
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| "first": "\u092e\u093e\u0928\u0935-\u0915 \u0943", |
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| "first": "\u092e\u093e\u0928\u0935", |
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| "first": "\u092e\u093e\u0928\u0935-\u0915 \u0943 \u093f", |
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| "first": "\u0915 \u0943 \u0924\u094d\u0930 \u093f\u092e", |
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| "raw_text": "\u092e\u093e\u0928\u0935 \u0915 \u0943 \u0924\u093f, \u092e\u093e\u0928\u0935\u0915 \u0943 \u0924\u093f, \u092e\u093e\u0928\u0935-\u0915 \u0943 \u0924\u093f, \u092e\u093e\u0928\u0935 \u0924\u0928\u0930\u094d\u092e\u093f \u093f \u0935\u0938\u094d\u093f\u0941 , \u092e\u093e\u0928\u0935-\u0915 \u0943 \u093f \u0935\u0938\u094d\u093f\u0941 , \u0915 \u0943 \u0924\u094d\u0930 \u093f\u092e \u0935\u0938\u094d\u093f\u0941 (Human work, man-made object, human -integrated object, artificial object)", |
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| "title": "(An object made or produced by man -A masterpiece of Mughal's era", |
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| "first": ": \u092e\u093e\u0928\u0935 \u0926\u094d\u0935\u093e\u0930\u093e \u092c\u0928\u093e\u0908 \u092f\u093e \u093f\u0948 \u092f\u093e\u0930 \u0915\u0940 \u0939 \u0941 \u0908 \u0935\u0938\u094d\u093f\u0941 \"\u092f\u0939 \u092e\u0941 \u0917\u0932\u0915\u093e\u0932\u0940\u0928 \u092e\u093e\u0928\u0935 \u0915 \u0943 \u0924\u093f", |
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| "raw_text": "Gloss/example: \u092e\u093e\u0928\u0935 \u0926\u094d\u0935\u093e\u0930\u093e \u092c\u0928\u093e\u0908 \u092f\u093e \u093f\u0948 \u092f\u093e\u0930 \u0915\u0940 \u0939 \u0941 \u0908 \u0935\u0938\u094d\u093f\u0941 \"\u092f\u0939 \u092e\u0941 \u0917\u0932\u0915\u093e\u0932\u0940\u0928 \u092e\u093e\u0928\u0935 \u0915 \u0943 \u0924\u093f \u0939\u0948 \" (An object made or produced by man - A masterpiece of Mughal's era.)", |
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| "text": "Drop-box to select a language (Indian languages) \uf0b7 Drop-box to select visualization options The output of the interface consists of: \uf0b7 A graphical view of all related words and concepts in a respective language for a given input word. (Screenshot 2) 6", |
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