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chapter 2 dissertation
A key component of this course is a significant research project, to be undertaken in pairs or individually. (Larger groups are permitted with the instructor's approval.) The goal of the final project is to develop a deep understanding in one or more of the areas studied in this course, and to conduct original research. Students are free to choose their partner, and their research project. Students must submit a proposal for their project, submit a progress report, give a project presentation, and submit a final project report.
Project proposal due Wed Oct 7, before class.Your proposal should be a 2-3 page document that includes sections on:
Project presentations will be done in-class on Monday November 30th.
Each project will have about 30 minutes. Aim for a 20 minute presentation to allow sufficient time for questions and discussion. You are not expected to have completed the research project by this date, but you are expected to have made tangible progress. The talk should be aimed at providing an overview of the problem, the outline of your approach to addressing the problem, and preliminary results.
As with the presentations throughout the class, your aim is not to explain every detail, but to communicate key points clearly.Final report
Final report due Wed Dec 9.
The final report will be in the style of a research conference paper, much like the papers we have been reading during the semester. An appropriate structure for the report would include an introduction, background/overview, technical content (e.g. presentation of the language and theorems), related work, and conclusion.
Email me a PDF of your final report by the deadline. The paper should be no more than 12 pages in ACM SIGPLAN format. I strongly recommend using LaTeX to write your final report, even if it means learning LaTeX (which you will need to do sometime soon anyway). I'm happy to help with LaTeX questions.Project ideas Here are some suggestions for research projects, to give you an idea of appropriate topics for your project. Projects must have some connection to CS252, but can incorporate ideas and techniques from other areas.
Identify a common pattern or problem in systems you have experience with. Explore language mechanisms to facilitate building such systems.See the additional reading list for more information about domain-specific languages. The following are some specific areas in which I've encountered some common bugs and/or coding patterns that language mechanisms may help address.
A Layered Drawing of a tree T is a drawing of T such that a vertex v of depth i has y-coordinate y(v) = -i. An algorithm constructs a drawing by computing the x-coordinates. We implement two methods for assigning x-coordinates. One is to set x(v) equal the rank of v in the inorder traversal of T, it works only for binary trees. Another one is by Reingold and Tilford (1983), it is a recursive drawing algorithm. For binary trees, after drawing the left and right subtrees, place the drawings of the subtrees at horizontal distance 2; place the root one level above and half-way between the children; however, if there is only one child, place the root at horizontal distance 1 from the child. This algorithm (Reingold and Tilford) has a straightforward generalization to rooted trees.
You can first set what kind trees (binary or rooted) you want to draw (the default is binary tree), and which drawing algorithm (Reingold-Tilford or inorder) you want to use (the default is Reigold-Tilford, and for rooted trees, you can use this algorithm only, the choice for inorder will be changed to R-T automatically), by clicking on named buttons below the first canvas. Then you can input your tree in the first canvas. You can either click on any point as the root or draw a line which will contains the root and its first child, then you can expand your tree by adding lines to any node. Note that if you choose a binary tree mode, any line to a node already with two children will be ignored. You are not allowed to draw the tree upward (the segment will be ignored). You may delete a node and all its children, to do this, you click on the delete button first to activate it (the button is checked), then click on the node you intend to delete. To deactivate delete function, click on the delete button again to make sure the button unchecked. After you draw a legal line (mouse-up), the layered drawing for you current tree will be displayed in the second canvas. You can move the displayed tree by clicking and dragging it.
You can read the book "Graph Drawing" by G. Battista, P. Eades, R. Tamassia, and I.G. Tollis. Draft available here.
Primary contact for this homework: Sujith Surendran [sujiths at cs dot wisc dot edu]
You must do this homework alone. Please staple multiple pages together.Problem 1 (4 points)
In your own words, explain how does a microarchitecture differ from an ISA. Why do you think we might want to design a different microarchitecture for an existing ISA?
The microarchitecture specifies how circuits are put together to create the computer. The Instruction Set Architecture (ISA) provides an interface which specifies what sort of instructions a computer supporting this interface can perform. We would do this for a number of reasons. Primarily, requirements could be different for different systems. For example, Servers require very high performace, so the microarchitecture should be designed accordingly. Servers does not put a major limitation on cost/ power. However other systems like mobile devices require a good performance at low cost, without significant power dissipation. The key to note here is that (other than hopefully an improvement in performance / cost / power) the actual user sees no difference when programming or running the computer.
Assume that we had a "black box," which takes two numbers as input and outputs their sum, as shown in Figure 1(a). Also assume that we had another box capable of multiplying two numbers together, as shown in Figure 1(b). We can connect these boxes together to compute p × (m + n), as shown in Figure 1(c).
Show how to connect these boxes together to compute:
Problem 6 (5 points)
Below are a few concepts which were covered in Chapter 1.
2 Format and Coverage Covers only material from thru (i.e. beginning with Probabilistic Parsing) Same format as midterm: –Short answers: 2-3 sentences –True/False: for false statements provide true correction that is not just the negation of the false statement, e.g.
3 –Good answer: The exam is on Dec 14. FALSE! The exam is on Dec 16. –Bad answer: The exam is on Dec 14. FALSE! The exam is not on Dec 14. Exercises Short essays: 2 essays, 3-5 paragraphs each The final will be only slightly longer than the midterm, although you will have the full 3h to complete it.
4 Probabilistic Parsing Problems with CFGs: –Rules unordered, many possible parses Solutions: –Weight the rules by their probabilities –But rules aren’t sensitive to lexical items or subcategorization frames –Add headwords to trees –Add subcategorization probabilities –Add complement/adjunct distinction –Etc.
5 Semantics Meaning Representations –Predicate/argument structure and FOPC –Problems with mapping to NL (e.g. and ^) Frame semantics Having Haver: S HadThing: Car –Problems with reasoning from representation
6 Subcategorization Frames and Thematic Roles What patterns of arguments can different verbs take? –NP likes NP –NP likes Inf-VP –NP likes NP Inf-VP What roles can arguments take? –Agent, Patient, Theme (The ice melted), Experiencer (Bill likes pizza), (Bill likes pizza), Stimulus (Bill likes pizza), Goal (Bill ran to Copley Square), Recipient (Bill gave the book to Mary), Instrument (Bill ate the burrito with a plastic spork), Location (Bill sits under the tree on Wednesdays)
7 Selectional Restrictions George assassinated the senator. The spider assassinated the fly *Cain assassinated Able. George broke the bank.
8 Lexical Semantics Lexemes Lexicon Wordnet: synsets Framenet: subcategorization frames/verb semantics
9 Word Relations Types of word relations –Homonymy: bank/bank –Homophones: red/read –Homographs: bass/bass –Polysemy: bank/sperm bank –Synonymy: big/large –Hyponym/hypernym: poodle/dog –Metonymy: (printing press)/the press –Meronymy: (wheel)/car –Metaphor: Nothing scares Google.
10 Word Sense Disambiguation Time flies like an arrow. Tasks: all-words vs. lexical sample Techniques: –Supervised, semi-supervised bootstrapping, unsupervised –Corpora needed –Features that are useful –Competitions and Evaluation methods Specific approaches: –Naïve Bayes, Decision Lists, Dictionary-based, Selectional Restrictions
11 Discourse Structure and Coherence Topic segmentation –Useful Features –Hearst’s TexTiling – how does it work? –Supervised methods – how do we evaluate? Coherence relations –Hobbs’ –Rhetorical Structure Theory – what are it’s problems?
12 Reference Terminology Referring expressions Discourse referents Anaphora and cataphora Coreference Antecendents Pronouns One-anaphora Definite and indefinite NPs Anaphoric chains
13 Constraints on Anaphoric Reference Salience Recency of mention: rule of 2 sentences Discourse structure Agreement Grammatical function Repeated mention Parallel construction Verb semantics/thematic roles Pragmatics
14 Algorithms for Coreference Resolution Lappin & Leas Hobbes Centering Theory Supervised approaches Evaluation
15 Information Extraction Template-based IE –Named Entity Tagging –Sequence-based relation tagging: supervised and bootstrapping –IE for Question Answering, e.g. biographical information (Biadsy’s `bouncing’ between Wikipedia and Google)
16 Information Retrieval Vector-Space model –Cosine similarity –TF/IDF weighting NIST competition retrieval tasks Techniques for improvement Metrics –Precision, recall, F-measure
17 Question Answering Factoid questions Useful Features Answer typing UT Dallas System
18 Summarization Types and approaches to summarization –Indicative vs. informative –Generative vs. extractive –Single vs. multi-document –Generic vs. user-focused Useful features Evaluation methods Newsblaster – how does it work? –Multi-document –Sentence fusion and ordering –Topic tracking
19 MT Multilingual challenges –Orthography, Lexical ambiguity, morphology, syntax MT Approaches: –The Pyramid –Statistical vs. Rule-based vs. Hybrid Evaluation metrics –Human vs. Bleu score –Criteria: fluency vs. accuracy
20 Dialogue Turns and Turn-taking Speech Acts and Dialogue Acts Grounding Intentional Structure: Centering Pragmatics –Presupposition –Conventional Implicature –Conversational Implicature