id int64 | question string | choices list | answer string |
|---|---|---|---|
1,041 | in a 2-dimensional model such as the FizHugh-Nagumo model, the auxiliary variable [mathjaxinline]w[/mathjaxinline] is necessary to implement a reset of the voltage after a spikein a nonlinear integrate-and-fire model, the auxiliary variable [mathjaxinline]w[/mathjaxinline] is necessary to implement a reset of the volta... | [
"in a 2-dimensional model such as the FizHugh-Nagumo model, the auxiliary variable [mathjaxinline]w[/mathjaxinline] is necessary to implement a reset of the voltage after a spike",
"in a nonlinear integrate-and-fire model, the auxiliary variable [mathjaxinline]w[/mathjaxinline] is necessary to implement a reset o... | A |
1,048 | 3. In an integrate-and-fire model, when the voltage hits the threshold ... | [
"the neuron fires a spike",
"the neuron can enter a state of refractoriness",
"the voltage is reset",
"the neuron explodes"
] | A |
1,052 | Choose the correct reasoning for justifying your answer in Q3: | [
"No matter what the weights are, the input scales with [mathjaxinline] N [/mathjaxinline]. Because every neuron is connected to every neuron, the fluctuations even scale as [mathjaxinline] N^2 [/mathjaxinline].",
"The weight scaling cancels out the dependence on [mathjaxinline] N [/mathjaxinline] in the input. Th... | C |
1,158 | Let $n$ be an integer such that $n\geq 2$ and let $A \in \R^{n imes n}$, and $xv \in \R^n$, consider the function $f(xv) = xv^ op A xv$ defined over $\R^n$. Which of the following is the gradient of the function $f$? | [
"$2 xv^\top A$",
"$2Axv$",
"$A^\top xv + Axv$",
"$2A^\top xv$"
] | C |
1,162 | You are using a neural net with $L$ layers, $K$ nodes per layer, and ReLUs as activation functions. Your input data has components in $[-1,0]$. You initialize all your weights to be Gaussians with mean 10 and variance 0.1 and all the bias terms are set to 0. You start optimizing using SGD. What will happen? | [
"the gradient is 0 and so nothing happens",
"the gradient is very large and so your steps are likely too large for the algorithm to converge",
"everything is fine",
"you cannot use a neural net for features that have negative components"
] | A |
1,171 | Every time you open the website \href{http://thispersondoesnotexist.com}{thispersondoesnotexist.com}, you see a fake picture of a person that was sampled from the distribution learned by a GAN. Which part of the GAN is deployed on this server? | [
"The discriminator.",
"The generator.",
"The discriminator and the generator.",
"Only the last layer of the discriminator."
] | B |
1,175 | Which of the following statements is extbf{incorrect} ? Training a model with $L_1$-regularization ... | [
"can reduce the storage cost of the final model.",
"is used to help escaping local minima during training.",
"can reduce overfitting.",
"can be named Lasso regression when in combination with an MSE loss function and a linear model."
] | B |
1,185 | Consider a matrix factorization problem of the form $\mathbf{X}=\mathbf{W Z}^{\top}$ to obtain an item-user recommender system where $x_{i j}$ denotes the rating given by $j^{\text {th }}$ user to the $i^{\text {th }}$ item . We use Root mean square error (RMSE) to gauge the quality of the factorization obtained. Selec... | [
"Given a new item and a few ratings from existing users, we need to retrain the already trained recommender system from scratch to generate robust ratings for the user-item pairs containing this item.",
"Regularization terms for $\\mathbf{W}$ and $\\mathbf{Z}$ in the form of their respective Frobenius norms are a... | D |
1,187 | We consider a classification problem on linearly separable data. Our dataset had an outlier---a point that is very far from the other datapoints in distance (and also far from margins in SVM but still correctly classified by the SVM classifier).
We trained the SVM, logistic regression and 1-nearest-... | [
"SVM",
"Logistic regression",
"1-nearest-neighbors classifier",
"All of them"
] | B |
1,200 | In principal component analysis, the left singular vectors $\mathbf{U}$ of a data matrix $\mathbf{X}$ of shape ( $d$ features, $n$ datapoints) are used to create a new data matrix $\mathbf{X}^{\prime}=\mathbf{U}^{\top} \mathbf{X}$. To achieve dimensionality reduction, we keep only certain rows of the matrix $\mathbf{X}... | [
"the lowest variance.",
"the highest variance.",
"smallest L2 norm.",
"L2 norm closest to 1"
] | B |
1,202 | Consider the Parametric ReLU function defined as
$$f(x) = \left\{egin{matrix}
x & extup{if}\; x > 0 \
ax & extup{otherwise}
\end{matrix}
ight.$$
where $a \in \R$ is an arbitrary number.
Which of the following statements is ... | [
"A subgradient exists even though $f(x)$ is not necessarily differentiable at $x=0$.",
"A subgradient does not exist at $x=0$.",
"If a subgradient exists, then it is not unique.",
"None of the mentioned answers."
] | D |
1,207 | Consider the loss function $L: \R^d o \R$, $L(\wv) = rac{eta}{2}\|\wv\|^2$, where $eta > 0$ is a constant. We run gradient descent on $L$ with a stepsize $\gamma > 0$ starting from some $\wv_0
eq 0$. Which of the statements below is true? | [
"Gradient descent converges to the global minimum for any stepsize $\\gamma > 0$.",
"Gradient descent with stepsize $\\gamma = \frac{2}{\beta}$ produces iterates that diverge to infinity ($\\|\\wv_t\\| \to \\infty$ as $t\to \\infty$).",
"Gradient descent converges in two steps for $\\gamma = \frac{1}{\beta}$ (i... | D |
1,210 | Consider a regression model where data $(x,y)$ is generated by input $x$ uniformly randomly sampled from $[0,1]$ and $y(x) = x^2 + \epsilon$,
where $\epsilon$ is random noise with mean 0 and variance 1.
Two models are carried out for regression:
model A is a trained quadratic function $... | [
"higher bias, higher variance.",
"higher bias, lower variance.",
"lower bias, higher variance.",
"lower bias, lower variance."
] | C |
1,213 | What \emph{alternates} in Alternating Least Squares for Matrix Factorization for a movie recommender system? | [
"recommendation steps and optimization steps",
"updates to user embeddings and updates to movie embeddings",
"expectation steps and maximization steps",
"updates based on different movie rating examples from the training set"
] | B |
1,214 | Let's imagine that every pet owner in Europe sends us their dog and cat data to train our model, so we have lots of training data. Which of the following is true about the possible optimizers used to train our model? We assume that the optimal hyperparameters are used for each optimizer.
| [
"Gradient descent steps are more computationally efficient, while Newton's method takes fewer steps to converge.",
"Gradient descent takes fewer steps to converge, while Newton steps are more computationally efficient.",
"Gradient descent and Newton's method take similar number of iterations to converge.",
"O... | A |
1,216 | You are doing your ML project. It is a regression task under a square loss. Your neighbor uses linear regression and least squares. You are smarter. You are using a neural net with 10 layers and activations functions $f(x)=3 x$. You have a powerful laptop but not a supercomputer. You are betting your neighbor a beer at... | [
"Because we use exactly the same scheme.",
"Because it is almost impossible to train a network with 10 layers without a supercomputer.",
"Because I should have used more layers.",
"Because I should have used only one layer."
] | A |
1,217 | Let $f:\R^D
ightarrow\R$ be an $L$-hidden layer multi-layer perceptron (MLP) such that
\[
f(xv)=\sigma_{L+1}ig(\wv^ op\sigma_L(\Wm_L\sigma_{L-1}(\Wm_{L-1}\dots\sigma_1(\Wm_1xv)))ig),
\]
with $\wv\in\R^{M}$, $\Wm_1\in\R^{M imes D}$ and $\... | [
"$C_{g, \frac{1}{2}}$ may have an accuracy significantly lower than $C_{f, \frac{1}{2}}$ on $T$",
"$C_{h, 0}$ may have an accuracy significantly lower than $C_{f, \frac{1}{2}}$ on $T$",
"$C_{q, 0}$ may have an accuracy significantly lower than $C_{f, \frac{1}{2}}$ on $T$",
"$C_{g, \frac{1}{2}}$, $C_{h, 0}$, a... | D |
1,218 | Binary logistic regression assumes a: | [
"Linear relationship between the input variables.",
"Linear relationship between the observations.",
"Linear relationship between the input variables and the logit (inverse of sigmoid) of the probability of the event that the outcome $Y=1$.",
"Linear relationship between the input variables and the probabilit... | C |
1,221 | Let $f_{\mathrm{MLP}}: \mathbb{R}^{d} \rightarrow \mathbb{R}$ be an $L$-hidden layer multi-layer perceptron (MLP) such that $$ f_{\mathrm{MLP}}(\mathbf{x})=\mathbf{w}^{\top} \sigma\left(\mathbf{W}_{L} \sigma\left(\mathbf{W}_{L-1} \ldots \sigma\left(\mathbf{W}_{1} \mathbf{x}\right)\right)\right) $$ with $\mathbf{w} \in ... | [
"The output layer weights are not used for computing the error of the hidden layer.",
"The weight changes are not proportional to the difference between the desired and actual outputs.",
"A standard technique to initialize the weights is to set them exactly to 0.",
"The weight change is also proportional to t... | D |
1,222 | Let the samples $\left\{\left(y_{n}, x_{n}\right)\right\}$ come from some fixed joint distribution $p(x, y)$, where $x_{n}$ and $y_{n}$ are scalars and both have zero mean. Consider linear regression, i.e., we want to predict $Y$ from $X$ by means of $f(x)=\alpha x$ and we consider a square loss. Meaningful regression ... | [
"(a) only if $X$ \"causes\" $Y$",
"(b) as long as $Y$ and $X$ have non-zero correlation",
"(c) only if $Y$ and $X$ are positively correlated, i.e., $\\mathbb{E}[X Y]>0$",
"(d) only if $Y$ and $X$ are negatively correlated, i.e., $\\mathbb{E}[X Y]<0$"
] | C |
1,226 | Does this learning rule allow for both potentiation and depression? | [
"No, because there aren't any negative terms.",
"Yes, because there are also negative terms.",
"No, because the negative terms are always smaller than the positive ones.",
"Yes, only because there is the last term with the power of four."
] | B |
1,241 | The above mentioned property of the energy function [mathjaxinline] H [/mathjaxinline] was proven explicitly in the exercises of this course. In an intermediate step of this proof we could write the energy change as | [
"The minus sign of the energy change [mathjaxinline] \\Delta H [/mathjaxinline] itself ensures the decay of the energy function. Thus it is always decreasing, i.e. it never increases.",
"The update dynamics includes the sign-function. Thus the product in the energy change [mathjaxinline] \\Delta H [/mathjaxinline... | B |
1,243 | We assume a pair-based STDP model formulated with traces: | [
"For pre-before-post the decay of the STDP window is exponential with time constant [mathjaxinline]\\tau_+[/mathjaxinline].",
"For pre-before-post the decay is a double exponential with time constants [mathjaxinline]\\tau_+[/mathjaxinline] and [mathjaxinline]\\tau_-[/mathjaxinline].",
"For pre-before-post the d... | A |
1,245 | The space constant of a passive cable is: | [
"[mathjaxinline]\\lambda=\\frac{r_m}{r_L}[/mathjaxinline]",
"[mathjaxinline]\\lambda=\\frac{r_L}{r_m}[/mathjaxinline]",
"[mathjaxinline]\\lambda=\\sqrt{\\frac{r_L}{r_m}}[/mathjaxinline]",
"[mathjaxinline]\\lambda=\\sqrt{\\frac{r_m}{r_L}}[/mathjaxinline]"
] | D |
1,249 | A spike train is generated by a homogenous Poisson process with rate 25Hz with time steps of 0.1 ms. | [
"The most likely interspike interval is 25 ms.",
"The most likely interspike interval is 40 ms.",
"The most likely interspike interval is 0.1 ms.",
"We cannot say."
] | C |
1,252 | Consider AdEx dynamical system: | [
"[mathjaxinline]u[/mathjaxinline]-nullcline moves horizontally",
"[mathjaxinline]u[/mathjaxinline]-nullcline moves vertically",
"[mathjaxinline]w[/mathjaxinline]-nullcline moves horizontally",
"[mathjaxinline]w[/mathjaxinline]-nullcline moves vertically"
] | B |
1,401 | If a short current pulse is injected into the dendrite: | [
"the voltage at the injection site is maximal immediately after the end of the injection.",
"the voltage at the dendritic injection site is maximal a few milliseconds after the end of the injection.",
"the voltage at the soma is maximal immediately after the end of the injection.",
"the voltage at the soma is... | A |
1,402 | A spike train is generated by an inhomogenous Poisson process with a rate that oscillates periodically (sine wave with 1Hz frequency) between 0 and 50Hz (mean 25Hz). A first spike has been fired at a time when the rate was at its maximum. Time steps are 0.1ms. | [
"The most likely interspike interval is 25 ms.",
"The most likely interspike interval is 40 ms.",
"The most likely interspike interval is 0.1 ms.",
"We cannot say."
] | C |
1,403 | Which statement is false in the context of recommender systems? | [
"Cold-start problem is a typical problem of user-based collaborative filtering",
"Matrix factorization can be interpreted as a combination of user-based and content-based collaborative filtering",
"In item-based collaborative filtering, the item similarities can be computed in advance",
"Content-based recomme... | B |
1,404 | Which of the following is correct regarding Louvain algorithm? | [
"It creates a hierarchy of communities with a common root",
"Clique is the only topology of nodes where the algorithm detects the same communities, independently of the starting point",
"If n cliques of the same order are connected cyclically with n-1 edges, then the algorithm will always detect the same commun... | C |
1,405 | Considering the transaction below, which one is false?
Transaction IDItems Bought1Tea2Tea, Yoghurt3Tea, Yoghurt, Kebap4Kebap5Tea, Kebap | [
"{Yoghurt, Kebap} has 20% support",
"{Tea} has the highest support",
"{Yoghurt} -> {Kebab} has 50% confidence",
"{Yoghurt} has the lowest support among all itemsets"
] | D |
1,406 | What is WRONG regarding the Transformer model? | [
"Its computation cannot be parallelized compared to LSTMs and other sequential models.",
"It uses a self-attention mechanism to compute representations of the input and output.",
"Its complexity is quadratic to the input size.",
"It captures the semantic context of the input."
] | A |
1,407 | If we run the Apriori algorithm on the following transaction database with minimal support count of 2, which of the itemsets will have a support count of 3?Transaction IDItemsT1{1,3,4}T2{2,3,5}T3{1,2,3,5}T4{2,5}T5{1,2,3,5} | [
"{1,5}",
"{2,3}",
"{2,5}",
"{1,2}"
] | B |
1,408 | When computing PageRank iteratively, the computation ends when: | [
"The norm of the difference of rank vectors of two subsequent iterations falls below a predefined threshold",
"The difference among the eigenvalues of two subsequent iterations falls below a predefined threshold",
"All nodes of the graph have been visited at least once",
"The probability of visiting an unseen... | A |
1,409 | Consider the document: “Information retrieval is the task of finding the documents satisfying the information needs of the user”
Using MLE to estimate the unigram probability model, what is P(the|Md) and P(information|Md)? | [
"1/16 and 1/16",
"1/12 and 1/12",
"1/4 and 1/8",
"1/3 and 1/6"
] | C |
1,410 | Let the first four retrieved documents be N N R R, where N denotes a non-relevant and R a relevant document. Then the MAP (Mean Average Precision) is: | [
"1/2",
"5/12",
"3/4",
"7/24"
] | B |
1,411 | Which one of the following is wrong. Schema mapping is used to: | [
"Overcome semantic heterogeneity",
"Reconcile different logical representations of the same domain",
"Optimize the processing of queries",
"Support schema evolution of databases"
] | C |
1,414 | Modularity clustering will end up always with a single community at the top level? | [
"true",
"Only for dense graphs",
"Only for connected graphs",
"never"
] | C |
1,416 | The inverse document frequency of a term can increase | [
"by adding the term to a document that contains the term",
"by removing a document from the document collection that does not contain the term",
"by adding a document to the document collection that contains the term",
"by adding a document to the document collection that does not contain the term"
] | D |
1,417 | Which of the following is wrong regarding Ontologies? | [
"We can create more than one ontology that conceptualize the same real-world entities",
"Ontologies help in the integration of data expressed in different models",
"Ontologies support domain-specific vocabularies",
"Ontologies dictate how semi-structured data are serialized"
] | D |
1,418 | In a Ranked Retrieval result, the result at position k is non-relevant and at k+1 is relevant. Which of the following is always true (P@k and R@k are the precision and recall of the result set consisting of the k top ranked documents)? | [
"P@k-1 > P@k+1",
"P@k-1 = P@k+1",
"R@k-1 < R@k+1",
"R@k-1 = R@k+1"
] | C |
1,419 | We want to return, from the two posting lists below, the top-2 documents matching a
query using Fagin’s algorithm with the aggregation function taken as the sum of the tf-idf weights. How many entries (total of both lists) are accessed in the first phase of the
algorithm performing round-robin starting at List 1 (i.e.,... | [
"4",
"6",
"8",
"10"
] | C |
1,420 | What is true regarding Fagin's algorithm? | [
"It performs a complete scan over the posting files",
"It provably returns the k documents with the largest aggregate scores",
"Posting files need to be indexed by TF-IDF weights",
"It never reads more than (kn)½ entries from a posting list"
] | B |
1,421 | Which of the following is true for Recommender Systems (RS)? | [
"Matrix Factorization can predict a score for any user-item combination in the dataset.",
"The complexity of the Content-based RS depends on the number of users",
" Item-based RS need not only the ratings but also the item features",
"Matrix Factorization is typically robust to the cold-start problem."
] | A |
1,422 | Which of the following is WRONG for Ontologies? | [
"Different information systems need to agree on the same ontology in order to interoperate.",
"They help in the integration of data expressed in different models.",
"They give the possibility to specify schemas for different domains.",
"They dictate how semi-structured data are serialized."
] | D |
1,423 | Why is non-discounted cumulative gain used as evaluation metrics for recommender systems | [
"because often only the top recommendations are considered by the user",
"because it is more accurate than retrieval metrics, like precision and recall",
"because it considers the predicted ratings of all items that have not been rated by the user",
"because it allows to consider the financial value of recomm... | A |
1,424 | What is the benefit of LDA over LSI? | [
"LSI is sensitive to the ordering of the words in a document, whereas LDA is not",
"LDA has better theoretical explanation, and its empirical results are in general better than LSI’s",
"LSI is based on a model of how documents are generated, whereas LDA is not",
"LDA represents semantic dimensions (topics, co... | B |
1,425 | Which of the following is true? | [
"High precision implies low recall",
"High precision hurts recall",
"High recall hurts precision",
"High recall implies low precisions"
] | B |
1,426 | Maintaining the order of document identifiers for vocabulary construction when partitioning the document collection is important | [
"in the index merging approach for single node machines",
"in the map-reduce approach for parallel clusters",
"in both",
"in neither of the two"
] | A |
1,427 | Which of the following is correct regarding Crowdsourcing? | [
"Random Spammers give always the same answer for every question",
"It is applicable only for binary classification problems",
"Honey Pot discovers all the types of spammers but not the sloppy workers",
"The output of Majority Decision can be equal to the one of Expectation-Maximization"
] | D |
1,428 | When computing PageRank iteratively, the computation ends when... | [
"The difference among the eigenvalues of two subsequent iterations falls below a predefined threshold",
"The norm of the difference of rank vectors of two subsequent iterations falls below a predefined threshold",
"All nodes of the graph have been visited at least once",
"The probability of visiting an unseen... | B |
1,429 | TransE is known to have difficulties in representing symmetric relationships r. Which of the following statements is correct for a symmetric relationship and provides insight for this problem? | [
"For all e1 , e2: \\( f(e_1, r, e_2) = f(e_2, r, e_1) \\)",
"For all e1 , e2: \\( f(e_1, r, e_2) = -f(e_2, r, e_1) \\)",
"\\( \\Sigma_{ e_1, e_2} f(e_1, r, e_2) + f(e_2, r, e_1) \\) is minimized if the embedding vector of r is large",
"\\( \\Sigma_{ e_1, e_2} f(e_1, r, e_2) + f(e_2, r, e_1) \\) is minimized ... | D |
1,430 | How does LSI querying work? | [
"The query vector is treated as an additional term; then cosine similarity is computed",
"The query vector is transformed by Matrix S; then cosine similarity is computed",
"The query vector is treated as an additional document; then cosine similarity is computed",
"The query vector is multiplied with an ortho... | C |
1,433 | Suppose that an item in a leaf node N exists in every path. Which one is correct? | [
"N co-occurs with its prefix in every transaction.",
"For every node P that is a parent of N in the fp tree, confidence(P->N) = 1",
"N’s minimum possible support is equal to the number of paths.",
"The item N exists in every candidate set."
] | C |
1,434 | In a Ranked Retrieval result, the result at position k is non-relevant and at k+1 is relevant. Which of the following is always true (P@k and R@k are the precision and recall of the result set consisting of the k top ranked documents)? | [
"P@k-1 > P@k+1",
"P@k-1 = P@k+1",
"R@k-1 < R@k+",
"R@k-1 = R@k+1"
] | C |
1,435 | Semi-structured data | [
"is always schema-less",
"always embeds schema information into the data",
"must always be hierarchically structured",
"can never be indexed"
] | B |
1,436 | How many among the listed classifiers can be used to derive probability estimate of the class label?
1NN, kNN, Rocchio, NB, fasttext | [
"1",
"2",
"3",
"4"
] | C |
1,438 | Given the following list of transactions: {apple,milk}, {milk, bread}, {apple, bread, milk}, {bread}, which of the following is correct? | [
"milk → apple has support ½ and confidence 1",
"milk → bread has support ½ and confidence 1",
"bread → milk has support ½ and confidence 1",
"apple → milk has support ½ and confidence 1"
] | D |
1,439 | For the number of times the apriori algorithm and the FPgrowth algorithm for association rule mining are scanning the transaction database the following is true | [
"fpgrowth has always strictly fewer scans than apriori",
"fpgrowth and apriori can have the same number of scans",
"apriori cannot have fewer scans than fpgrowth",
"all three above statements are false"
] | B |
1,441 | Given the following teleporting matrix (Ε) for nodes A, B and C:[0 ½ 0][0 0 0][0 ½ 1]and making no assumptions about the link matrix (R), which of the following is correct:(Reminder: columns are the probabilities to leave the respective node.) | [
"A random walker can never reach node A",
"A random walker can never leave node A",
"A random walker can always leave node C",
"A random walker can always leave node B"
] | D |
1,442 | Suppose that an item in a leaf node N exists in every path. Which one is correct? | [
"N co-occurs with its prefix in every transaction.",
"For every node p that is a parent of N in the fp tree, confidence(p->n) = 1 c.",
"N’s minimum possible support is equal to the number of paths.",
"The item N exists in every candidate set."
] | C |
1,443 | What is the support of the itemset {beer, chocolate} and the confidence of the rule {chocolate} → {beer} in the dataset below?TID: Items BoughtT1: milk, butter, beerT2: milk, diaper, beer, eggsT3: butter, diaper, beer, chocolate
T4: milk, butter, diaper, beerT5: milk, butter, diaper, chocolate
| [
"0.2/0.25",
"0.4/0.5",
"0.2/0.5",
"0.4/0.25\n\n\n\n"
] | C |
1,444 | Which of the following methods does not exploit statistics on the co-occurrence of words in a text? | [
"Word embeddings\n\n\n",
"Transformers\n\n\n",
"Vector space retrieval\n\n\n",
"Fasttext"
] | C |
1,445 | Which of the following is true regarding inverted files? | [
"The space requirement for the postings file is O(nβ), where β is generally between 0.4 and 0.6",
"Varying length compression is used to reduce the size of the index file",
"Inverted files prioritize efficiency on insertion over efficiency on search",
"Storing differences among word addresses reduces the size... | D |
1,446 | The loss function is minimized | [
"By modifying the word embedding vectors",
"By changing the sampling strategy for negative samples",
"By carefully choosing the positive samples",
"By sampling non-frequent word-context pairs more frequently"
] | A |
1,447 | Fundamentally, why clustering is considered an unsupervised machine learning technique? | [
"Number of clusters are not known.",
"The class labels are not known.",
"The features are not known.",
"The clusters can be different with different initial parameters."
] | B |
1,449 | Which attribute gives the best split?A1PNa44b44A2PNx51y33A3PNt61j23 | [
"A1",
"A3",
"A2",
"All the same"
] | B |
1,450 | Suppose that q is density reachable from p. The chain of points that ensure this relationship are {t,u,g,r} Which one is FALSE? | [
"{t,u,g,r} have to be all core points.",
"p and q will also be density-connected",
"p has to be a core point",
"q has to be a border point"
] | D |
1,451 | In User-Based Collaborative Filtering, which of the following is correct, assuming that all the ratings are positive? | [
"Pearson Correlation Coefficient and Cosine Similarity have different value range, but return the same similarity ranking for the users",
"If the ratings of two users have both variance equal to 0, then their Cosine Similarity is maximized",
"Pearson Correlation Coefficient and Cosine Similarity have the same v... | B |
1,452 | The term frequency of a term is normalized | [
"by the maximal frequency of all terms in the document",
"by the maximal frequency of the term in the document collection",
"by the maximal frequency of any term in the vocabulary",
"by the maximal term frequency of any document in the collection"
] | A |
1,453 | Which of the following statements on Latent Semantic Indexing (LSI) and Word Embeddings (WE) is false? | [
"LSI is deterministic (given the dimension), whereas WE is not",
"LSI does not depend on the order of words in the document, whereas WE does",
"The dimensions of LSI can be interpreted as concepts, whereas those of WE cannot",
"LSI does take into account the frequency of words in the documents, whereas WE wit... | D |
1,457 | Tugrulcan wanted to plan his next summer vacation so he wrote “best beaches” to his favourite search engine. Little did he know, his favourite search engine was using pseudo-relevance feedback and the top-k documents that are considered relevant were about the beaches only in Turkey. What is this phenomenon called? | [
"Query Bias",
"Query Confounding",
"Query Drift",
"Query Malfunction"
] | C |
1,458 | When compressing the adjacency list of a given URL, a reference list | [
"Is chosen from neighboring URLs that can be reached in a small number of hops",
"May contain URLs not occurring in the adjacency list of the given URL",
"Lists all URLs not contained in the adjacency list of given URL",
"All of the above"
] | B |
1,461 | Data being classified as unstructured or structured depends on the: | [
"Degree of abstraction",
"Level of human involvement",
"Type of physical storage",
"Amount of data "
] | A |
1,463 | Suppose you have a search engine that retrieves the top 100 documents and
achieves 90% precision and 20% recall. You modify the search engine to
retrieve the top 200 and mysteriously, the precision stays the same. Which one
is CORRECT? | [
"The recall becomes 10%",
"The number of relevant documents is 450",
"The F-score stays the same",
"This is not possible"
] | B |
1,464 | Which of the following is true for community detection in social graphs? | [
"The Louvain algorithm always creates a hierarchy of communities with a common root.",
"The Louvain algorithm is efficient for small networks, while the Girvan-Newman algorithm is efficient for large networks.",
"If n cliques of the same order are connected cyclically with n edges, then the Louvain algorithm wi... | C |
1,465 | In the χ2 statistics for a binary feature, we obtain P(χ2 | DF = 1) > 0.05. This means in this case, it is assumed: | [
"That the class labels depends on the feature",
"That the class label is independent of the feature",
"That the class label correlates with the feature",
"None of the above"
] | B |
1,467 | Which of the following is correct regarding the use of Hidden Markov Models (HMMs) for entity recognition in text documents? | [
"The cost of learning the model is quadratic in the lengths of the text.",
"The cost of predicting a word is linear in the lengths of the text preceding the word.",
"An HMM model can be built using words enhanced with morphological features as input.",
"The label of one word is predicted based on all the prev... | C |
1,468 | 10 itemsets out of 100 contain item A, of which 5 also contain B. The rule A -> B has: | [
"5% support and 10% confidence",
"10% support and 50% confidence",
"5% support and 50% confidence",
"10% support and 10% confidence"
] | C |
1,469 | Which of the following is correct regarding the use of Hidden Markov Models (HMMs) for entity recognition in text documents? | [
"HMMs cannot predict the label of a word that appears only in the test set",
"If the smoothing parameter λ is equal to 1, the emission probabilities for all the words in the test set will be equal",
"When computing the emission probabilities, a word can be replaced by a morphological feature (e.g., the number o... | C |
1,470 | A basic statement in RDF would be expressed in the relational data model by a table | [
"with one attribute",
"with two attributes",
"with three attributes",
"cannot be expressed in the relational data model"
] | B |
1,471 | Which of the following statements is wrong regarding RDF? | [
"An RDF statement would be expressed in SQL as a tuple in a table",
"Blank nodes in RDF graphs correspond to the special value NULL in SQL",
"The object value of a type statement corresponds to a table name in SQL",
"RDF graphs can be encoded as SQL databases"
] | B |
1,472 | The number of non-zero entries in a column of a term-document matrix indicates: | [
"how many terms of the vocabulary a document contains",
"how often a term of the vocabulary occurs in a document",
"how relevant a term is for a document ",
"none of the other responses is correct"
] | A |
1,473 | If t has no Hypernym | [
"It is a root concept",
"It cannot match c such as t and X",
"It is identical to the initial root concept",
"It is a basic concept"
] | A |
1,474 | Which of the following is true? | [
"Exploiting locality with gap encoding may increase the size of an adjacency list",
"Exploiting similarity with reference lists may increase the size of an adjacency list",
"Both of the above is true",
"None of the above is true"
] | A |
1,475 | What is TRUE regarding Fagin's algorithm? | [
"Posting files need to be indexed by TF-IDF weights",
"It performs a complete scan over the posting files",
"It never reads more than (kn)1⁄2 entries from a posting list",
"It provably returns the k documents with the largest aggregate scores"
] | D |
1,476 | A false negative in sampling can only occur for itemsets with support smaller than | [
"the threshold s",
"p*s",
"p*m",
"None of the above"
] | D |
1,477 | Why is XML a document model? | [
"It supports application-specific markup",
"It supports domain-specific schemas",
"It has a serialized representation",
"It uses HTML tags"
] | C |
1,478 | What is TRUE regarding the Multi-head Self-attention mechanism? | [
"Its computation cannot be parallelized compared to LSTMs and other sequential models.",
"It gives the Transformer the ability to learn different aspects of the meanings of each word.",
"LSTMs have larger memory than models with self-attention.",
"Its complexity is linear to the input size."
] | B |
1,481 | Suppose you have a search engine that retrieves the top 100 documents and achieves 90% precision and 20% recall. You modify the search engine to retrieve the top 200, and mysteriously, the precision stays the same. Which one is correct? | [
"The recall becomes 10%",
"The number of relevant documents is 450",
"The F-score stays the same",
"This is not possible"
] | B |
1,482 | A retrieval model attempts to capture | [
"the interface by which a user is accessing information",
"the importance a user gives to a piece of information for a query",
"the formal correctness of a query formulation by user",
"the structure by which a document is organised"
] | B |
1,485 | When computing HITS, the initial values | [
"Are set all to 1",
"Are set all to 1/n",
"Are set all to 1/sqrt(n)",
"Are chosen randomly"
] | C |
1,486 | Which of the following is correct regarding schemas and ontologies? | [
" An ontology is created from constructing mappings between schemas",
"Ontologies can be used for reasoning about different schemas",
"Ontologies always require a schema",
"Semi-structured data cannot have a schema"
] | B |
1,488 | Given the 2-itemsets {1,2}, {1,5}, {2,5}, {1,4}, {1,3}, when generating the 3-itemsets we will: | [
"Generate 5 3-itemsets after the join and 2 3-itemsets after the prune",
"Generate 6 3-itemsets after the join and 1 3-itemsets after the prune",
"Generate 4 3-itemsets after the join and 1 3-itemsets after the prune",
"Generate 4 3-itemsets after the join and 2 3-itemsets after the prune"
] | B |
1,490 | When indexing a document collection using an inverted file, the main space requirement is implied by | [
"The access structure",
"The vocabulary",
"The index file",
"The postings file"
] | D |
1,492 | Which of the following is correct regarding prediction models? | [
"A high bias is a sign of overfitting.",
"A high variance is a sign of underfitting.",
"In low data regime, complex models tend to perform better.",
"Simple models have higher bias than complex models."
] | D |
1,493 | For a user that has not done any ratings, which method can make a prediction? | [
"User-based collaborative RS",
"Item-based collaborative RS",
"Content-based RS",
"None of the above"
] | D |
1,495 | Which statement is correct? | [
"The Viterbi algorithm works because words are independent in a sentence",
"The Viterbi algorithm works because it is applied to an HMM model that makes an independence assumption on the word dependencies in sentences",
"The Viterbi algorithm works because it makes an independence assumption on the word depende... | B |
1,497 | Recall can be defined as: | [
"P(relevant documents | retrieved documents)",
"P(retrieved documents relevant documents)",
"P(retrieved documents number of documents)",
"P(relevant documents number of documents)"
] | B |
1,498 | Which of the following is WRONG about inverted files? (Slide 24,28 Week 3) | [
"The space requirement for the postings file is O(n)",
"Variable length compression is used to reduce the size of the index file",
"The index file has space requirement of O(n^beta), where beta is about 1⁄2",
"Storing differences among word addresses reduces the size of the postings file"
] | B |
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